Thomas Lukasiewicz : Publications
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[1]
(Non−)Convergence Results for Predictive Coding Networks
Simon Frieder and Thomas Lukasiewicz
In Kamalika Chaudhuri‚ Stefanie Jegelka‚ Le Song‚ Csaba Szepesvari‚ Gang Niu and Sivan Sabato, editors, Proceedings of the 39th International Conference on Machine Learning‚ ICML 2022‚ Baltimore‚ Maryland‚ USA‚ 17−23 July 2022. Vol. 162 of Proceedings of Machine Learning Research. Pages 6793–6810. PMLR. July, 2022.
Details about (Non−)Convergence Results for Predictive Coding Networks | BibTeX data for (Non−)Convergence Results for Predictive Coding Networks | Link to (Non−)Convergence Results for Predictive Coding Networks
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[2]
A Combination of Boolean Games with Description Logics for Automated Multi−Attribute Negotiation
Thomas Lukasiewicz and Azzurra Ragone
In Bernardo Cuenca Grau‚ Ian Horrocks‚ Boris Motik and Ulrike Sattler, editors, Proceedings of the 22nd International Workshop on Description Logics‚ DL 2009‚ Oxford‚ UK‚ July 27−30‚ 2009. Vol. 477 of CEUR Workshop Proceedings. CEUR−WS.org. 2009.
Details about A Combination of Boolean Games with Description Logics for Automated Multi−Attribute Negotiation | BibTeX data for A Combination of Boolean Games with Description Logics for Automated Multi−Attribute Negotiation | Download (pdf) of A Combination of Boolean Games with Description Logics for Automated Multi−Attribute Negotiation
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[3]
A Data Model and Algebra for Probabilistic Complex Values
Thomas Eiter‚ Thomas Lukasiewicz and Michael Walter
In Annals of Mathematics and Artificial Intelligence. Vol. 33. No. 2–4. Pages 205–252. December, 2001.
Details about A Data Model and Algebra for Probabilistic Complex Values | BibTeX data for A Data Model and Algebra for Probabilistic Complex Values | Link to A Data Model and Algebra for Probabilistic Complex Values
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[4]
A Framework for Representing Ontology Mappings under Probabilities and Inconsistency
Andrea Calì‚ Thomas Lukasiewicz‚ Livia Predoiu and Heiner Stuckenschmidt
In Fernando Bobillo‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Francis Fung‚ Thomas Lukasiewicz‚ Trevor Martin‚ Matthias Nickles‚ Yun Peng‚ Michael Pool‚ Pavel Smrz and Peter Vojtás, editors, Proceedings of the 3rd ISWC Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2007‚ Busan‚ Korea‚ November 12‚ 2007. Vol. 327 of CEUR Workshop Proceedings. CEUR−WS.org. 2008.
Details about A Framework for Representing Ontology Mappings under Probabilities and Inconsistency | BibTeX data for A Framework for Representing Ontology Mappings under Probabilities and Inconsistency | Download (pdf) of A Framework for Representing Ontology Mappings under Probabilities and Inconsistency
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[5]
A General Datalog−Based Framework for Tractable Query Answering over Ontologies
Andrea Calì‚ Georg Gottlob and Thomas Lukasiewicz
In Jan Paredaens and Jianwen Su, editors, Proceedings of the 28th ACM Symposium on Principles of Database Systems‚ PODS 2009‚ Providence‚ Rhode Island‚ USA‚ June 19 − July 1‚ 2009. Pages 77−86. ACM Press. 2009.
Details about A General Datalog−Based Framework for Tractable Query Answering over Ontologies | BibTeX data for A General Datalog−Based Framework for Tractable Query Answering over Ontologies | Link to A General Datalog−Based Framework for Tractable Query Answering over Ontologies
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[6]
A General Datalog−Based Framework for Tractable Query Answering over Ontologies
Andrea Calì‚ Georg Gottlob and Thomas Lukasiewicz
In Journal of Web Semantics. Vol. 14. Pages 57–83. July, 2012.
Details about A General Datalog−Based Framework for Tractable Query Answering over Ontologies | BibTeX data for A General Datalog−Based Framework for Tractable Query Answering over Ontologies | Link to A General Datalog−Based Framework for Tractable Query Answering over Ontologies
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[7]
A General Datalog−Based Framework for Tractable Query Answering over Ontologies
Andrea Calì‚ Georg Gottlob and Thomas Lukasiewicz
No. RR−10−21. OUCL. March, 2012.
Details about A General Datalog−Based Framework for Tractable Query Answering over Ontologies | BibTeX data for A General Datalog−Based Framework for Tractable Query Answering over Ontologies | Download (pdf) of A General Datalog−Based Framework for Tractable Query Answering over Ontologies
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[8]
A General Datalog−Based Framework for Tractable Query Answering over Ontologies (Extended Abstract)
Andrea Calì‚ Georg Gottlob and Thomas Lukasiewicz
In Valeria De Antonellis‚ Silvana Castano‚ Barbara Catania and Giovanna Guerrini, editors, Proceedings of the 17th Italian Symposium on Advanced Database Systems‚ SEBD 2009‚ Camogli‚ Italy‚ June 21−24‚ 2009. Pages 29−36. Edizioni Seneca. 2009.
Details about A General Datalog−Based Framework for Tractable Query Answering over Ontologies (Extended Abstract) | BibTeX data for A General Datalog−Based Framework for Tractable Query Answering over Ontologies (Extended Abstract) | Download (pdf) of A General Datalog−Based Framework for Tractable Query Answering over Ontologies (Extended Abstract)
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[9]
A General Framework for Inconsistency−Tolerant Query Answering in Datalog+⁄−
Thomas Lukasiewicz‚ Maria Vanina Martinez and Gerardo I. Simari
No. RR−14−04. DCS. 2014.
Details about A General Framework for Inconsistency−Tolerant Query Answering in Datalog+⁄− | BibTeX data for A General Framework for Inconsistency−Tolerant Query Answering in Datalog+⁄− | Download (pdf) of A General Framework for Inconsistency−Tolerant Query Answering in Datalog+⁄−
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[10]
A Logical Toolbox for Ontological Reasoning
Andrea Calì‚ Georg Gottlob‚ Thomas Lukasiewicz and Andreas Pieris
In SIGMOD Record. Vol. 40. No. 3. Pages 5–14. 2011.
Details about A Logical Toolbox for Ontological Reasoning | BibTeX data for A Logical Toolbox for Ontological Reasoning | Link to A Logical Toolbox for Ontological Reasoning
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[11]
A Novel Characterization of the Complexity Class Θ^P_k Based on Counting and Comparison
Thomas Lukasiewicz and Enrico Malizia
In Theoretical Computer Science. Vol. 694. Pages 21–33. September, 2017.
Details about A Novel Characterization of the Complexity Class Θ^P_k Based on Counting and Comparison | BibTeX data for A Novel Characterization of the Complexity Class Θ^P_k Based on Counting and Comparison | Link to A Novel Characterization of the Complexity Class Θ^P_k Based on Counting and Comparison
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[12]
A Novel Combination of Answer Set Programming with Description Logics for the Semantic Web
Thomas Lukasiewicz
In Enrico Franconi‚ Michael Kifer and Wolfgang May, editors, Proceedings of the 4th European Semantic Web Conference‚ ESWC 2007‚ Innsbruck‚ Austria‚ June 3−7‚ 2007. Vol. 4519 of Lecture Notes in Computer Science. Pages 384−398. Springer. 2007.
Details about A Novel Combination of Answer Set Programming with Description Logics for the Semantic Web | BibTeX data for A Novel Combination of Answer Set Programming with Description Logics for the Semantic Web | Link to A Novel Combination of Answer Set Programming with Description Logics for the Semantic Web
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[13]
A Novel Combination of Answer Set Programming with Description Logics for the Semantic Web
Thomas Lukasiewicz
In IEEE Transactions on Knowledge and Data Engineering (TKDE). Vol. 22. No. 11. Pages 1577–1592. November, 2010.
Details about A Novel Combination of Answer Set Programming with Description Logics for the Semantic Web | BibTeX data for A Novel Combination of Answer Set Programming with Description Logics for the Semantic Web | Link to A Novel Combination of Answer Set Programming with Description Logics for the Semantic Web
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[14]
A Stable‚ Fast‚ and Fully Automatic Learning Algorithm for Predictive Coding Networks
Tommaso Salvatori‚ Yuhang Song‚ Yordan Yordanov‚ Beren Millidge‚ Lei Sha‚ Cornelius Emde‚ Zhenghua Xu‚ Rafal Bogacz and Thomas Lukasiewicz
In Proceedings of the 12th International Conference on Learning Representations‚ ICLR 2024‚ Vienna‚ Austria‚ 7–11 May 2024. May, 2024.
Details about A Stable‚ Fast‚ and Fully Automatic Learning Algorithm for Predictive Coding Networks | BibTeX data for A Stable‚ Fast‚ and Fully Automatic Learning Algorithm for Predictive Coding Networks
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[15]
A Surprisingly Robust Trick for the Winograd Schema Challenge
Vid Kocijan‚ Ana−Maria Cretu‚ Oana−Maria Camburu‚ Yordan Yordanov and Thomas Lukasiewicz
In Anna Korhonen and David Traum, editors, Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics‚ ACL 2019‚ Florence‚ Italy‚ July 28 − August 2‚ 2019. Association for Computational Linguistics. July, 2019.
Details about A Surprisingly Robust Trick for the Winograd Schema Challenge | BibTeX data for A Surprisingly Robust Trick for the Winograd Schema Challenge | Link to A Surprisingly Robust Trick for the Winograd Schema Challenge
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[16]
A Theoretical Framework for Inference and Learning in Predictive Coding Networks
Beren Millidge‚ Yuhang Song‚ Tommaso Salvatori‚ Thomas Lukasiewicz and Rafal Bogacz
In Proceedings of the 11th International Conference on Learning Representations‚ ICLR 2023‚ Kigali‚ Rwanda‚ 1–5 May 2023. OpenReview.net. May, 2023.
Details about A Theoretical Framework for Inference and Learning in Predictive Coding Networks | BibTeX data for A Theoretical Framework for Inference and Learning in Predictive Coding Networks | Link to A Theoretical Framework for Inference and Learning in Predictive Coding Networks
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[17]
A Tutorial on Query Answering and Reasoning over Probabilistic Knowledge Bases
İsmail İlkan Ceylan and Thomas Lukasiewicz
In Claudia d'Amato and Martin Theobald, editors, Reasoning Web. Learning‚ Uncertainty‚ Streaming‚ and Scalability — 14th International Summer School 2018‚ Esch−sur−Alzette‚ Luxembourg‚ September 22−26‚ 2018‚ Tutorial Lectures. Vol. 11078 of Lecture Notes in Computer Science. Pages 35–77. Springer. August, 2018.
Details about A Tutorial on Query Answering and Reasoning over Probabilistic Knowledge Bases | BibTeX data for A Tutorial on Query Answering and Reasoning over Probabilistic Knowledge Bases | Link to A Tutorial on Query Answering and Reasoning over Probabilistic Knowledge Bases
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[18]
Adaptive Multi−Agent Programming in GTGolog
Alberto Finzi and Thomas Lukasiewicz
In Gerhard Brewka‚ Silvia Coradeschi‚ Anna Perini and Paolo Traverso, editors, Proceedings of the 17th European Conference on Artificial Intelligence‚ ECAI 2006‚ Riva del Garda‚ Italy‚ August 29 − September 1‚ 2006. Vol. 141 of Frontiers in Artificial Intelligence and Applications. Pages 753−754. IOS Press. 2006.
Details about Adaptive Multi−Agent Programming in GTGolog | BibTeX data for Adaptive Multi−Agent Programming in GTGolog | Download (pdf) of Adaptive Multi−Agent Programming in GTGolog
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[19]
Adaptive Multi−agent Programming in GTGolog
Alberto Finzi and Thomas Lukasiewicz
In Christian Freksa‚ Michael Kohlhase and Kerstin Schill, editors, Proceedings of the 29th German Conference on Artificial Intelligence‚ KI 2006‚ Bremen‚ Germany‚ June 14−17‚ 2006. Vol. 4314 of Lecture Notes in Computer Science. Pages 389−403. Springer. 2007.
Details about Adaptive Multi−agent Programming in GTGolog | BibTeX data for Adaptive Multi−agent Programming in GTGolog | Link to Adaptive Multi−agent Programming in GTGolog
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[20]
Adaptive−Masking Policy with Deep Reinforcement Learning for Self−Supervised Medical Image Segmentation
Gang Xu‚ Shengxin Wang‚ Thomas Lukasiewicz and Zhenghua Xu
In Proceedings of the IEEE International Conference on Multimedia and Expo‚ ICME 2023‚ Brisbane‚ Australia‚ July 10−14‚ 2023. IEEE. 2023.
Details about Adaptive−Masking Policy with Deep Reinforcement Learning for Self−Supervised Medical Image Segmentation | BibTeX data for Adaptive−Masking Policy with Deep Reinforcement Learning for Self−Supervised Medical Image Segmentation
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[21]
An Approach to Probabilistic Data Integration for the Semantic Web
Andrea Calì and Thomas Lukasiewicz
In Paulo Cesar G. da Costa‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Francis Fung and Michael Pool, editors, Proceedings of the 2nd ISWC Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2006‚ Athens‚ Georgia‚ USA‚ November 5‚ 2006. Vol. 218 of CEUR Workshop Proceedings. CEUR−WS.org. 2006.
Details about An Approach to Probabilistic Data Integration for the Semantic Web | BibTeX data for An Approach to Probabilistic Data Integration for the Semantic Web | Download (pdf) of An Approach to Probabilistic Data Integration for the Semantic Web
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[22]
An Approach to Probabilistic Data Integration for the Semantic Web
Andrea Calì and Thomas Lukasiewicz
In Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Matthias Nickles and Michael Pool, editors, Uncertainty Reasoning for the Semantic Web I‚ ISWC International Workshops‚ URSW 2005−2007‚ Revised Selected and Invited Papers. Vol. 5327 of Lecture Notes in Computer Science. Pages 52−65. Springer. 2008.
Details about An Approach to Probabilistic Data Integration for the Semantic Web | BibTeX data for An Approach to Probabilistic Data Integration for the Semantic Web | Link to An Approach to Probabilistic Data Integration for the Semantic Web
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[23]
An Empirical Analysis of Parameter−Efficient Methods for Debiasing Pre−Trained Language Models
Zhongbin Xie and Thomas Lukasiewicz
In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics‚ ACL 2023‚ Toronto‚ Canada‚ July 9–14‚ 2023. Association for Computational Linguistics. July, 2023.
Details about An Empirical Analysis of Parameter−Efficient Methods for Debiasing Pre−Trained Language Models | BibTeX data for An Empirical Analysis of Parameter−Efficient Methods for Debiasing Pre−Trained Language Models
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[24]
An Explainable Transformer−Based Deep Learning Model for the Prediction of Incident Heart Failure
Shishir Rao‚ Yikuan Li‚ Rema Ramakrishnan‚ Abdelaali Hassaine‚ Dexter Canoy‚ John Cleland‚ Thomas Lukasiewicz‚ Gholamreza Salimi−Khorshidi and Kazem Rahimi
In IEEE Journal of Biomedical and Health Informatics. Vol. 26. No. 7. Pages 3362−3372. February, 2022.
Details about An Explainable Transformer−Based Deep Learning Model for the Prediction of Incident Heart Failure | BibTeX data for An Explainable Transformer−Based Deep Learning Model for the Prediction of Incident Heart Failure | Link to An Explainable Transformer−Based Deep Learning Model for the Prediction of Incident Heart Failure
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[25]
An Ontology−Based Deep Learning Approach for Knowledge Graph Completion with Fresh Entities
Elvira Amador−Domı́nguez‚ Patrick Hohenecker‚ Thomas Lukasiewicz‚ Daniel Manrique and Emilio Serrano
In Francisco Herrera‚ Kenji Matsui and Sara Rodríguez Gonzalez, editors, Proceedings of the 16th International Conference on Distributed Computing and Artificial Intelligence (DCAI 2019)‚ Avila‚ Spain‚ June 26−28‚ 2019. Springer. June, 2019.
Details about An Ontology−Based Deep Learning Approach for Knowledge Graph Completion with Fresh Entities | BibTeX data for An Ontology−Based Deep Learning Approach for Knowledge Graph Completion with Fresh Entities | Link to An Ontology−Based Deep Learning Approach for Knowledge Graph Completion with Fresh Entities
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[26]
An Ontology−Based Deep Learning Approach for Triple Classification with Out−of−Knowledge−Base Entities
Elvira Amador−Domı́nguez‚ Emilio Serrano‚ Daniel Manrique‚ Patrick Hohenecker and Thomas Lukasiewicz
In Information Sciences. Vol. 564. Pages 85–102. July, 2021.
Details about An Ontology−Based Deep Learning Approach for Triple Classification with Out−of−Knowledge−Base Entities | BibTeX data for An Ontology−Based Deep Learning Approach for Triple Classification with Out−of−Knowledge−Base Entities | Link to An Ontology−Based Deep Learning Approach for Triple Classification with Out−of−Knowledge−Base Entities
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[27]
Answering EL Queries in the Presence of Preferences
İsmail İlkan Ceylan‚ Thomas Lukasiewicz and Rafael Peñaloza
In Diego Calvanese and Boris Konev, editors, Proceedings of the 28th International Workshop on Description Logics‚ DL 2015‚ Athens‚ Greece‚ June 7−10‚ 2015. Vol. 1350 of CEUR Workshop Proceedings. Pages 380−383. CEUR−WS.org. 2015.
Details about Answering EL Queries in the Presence of Preferences | BibTeX data for Answering EL Queries in the Presence of Preferences | Download (pdf) of Answering EL Queries in the Presence of Preferences
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[28]
Answering Ontological Ranking Queries Based on Subjective Reports
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Cristian Molinaro‚ Livia Predoiu and Gerardo Simari
In Thomas Lukasiewicz‚ Rafael Peñaloza and Anni−Yasmin Turhan, editors, Proceedings of the 1st Workshop on Logics for Reasoning about Preferences‚ Uncertainty‚ and Vagueness‚ PRUV 2014‚ Vienna‚ Austria‚ July 23−24‚ 2014. Vol. 1205 of CEUR Workshop Proceedings. Pages 127−140. CEUR−WS.org. 2014.
Details about Answering Ontological Ranking Queries Based on Subjective Reports | BibTeX data for Answering Ontological Ranking Queries Based on Subjective Reports | Download (pdf) of Answering Ontological Ranking Queries Based on Subjective Reports
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[29]
Answering Ontological Ranking Queries based on Subjective Reports
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Cristian Molinaro‚ Livia Predoiu and Gerardo I. Simari
In Umberto Straccia and Andrea Calì, editors, Proceedings of the 8th International Conference on Scalable Uncertainty Management‚ SUM 2014‚ Oxford‚ UK‚ September 15−17‚ 2014. Vol. 8720 of Lecture Notes in Computer Science. Pages 223−236. Springer. 2014.
Details about Answering Ontological Ranking Queries based on Subjective Reports | BibTeX data for Answering Ontological Ranking Queries based on Subjective Reports | Link to Answering Ontological Ranking Queries based on Subjective Reports
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[30]
Approximate Classification of Semantically Annotated Web Resources Exploiting Pseudo−Metrics Induced by Local Models
Claudia d'Amato‚ Nicola Fanizzi‚ Floriana Esposito and Thomas Lukasiewicz
In Proceedings of the 2009 IEEE/WIC/ACM International Conference on Web Intelligence‚ WI 2009‚ Milan‚ Italy‚ 15−18 September 2009. Pages 689−692. IEEE Computer Society. 2009.
Details about Approximate Classification of Semantically Annotated Web Resources Exploiting Pseudo−Metrics Induced by Local Models | BibTeX data for Approximate Classification of Semantically Annotated Web Resources Exploiting Pseudo−Metrics Induced by Local Models | Link to Approximate Classification of Semantically Annotated Web Resources Exploiting Pseudo−Metrics Induced by Local Models
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[31]
Arena: A General Evaluation Platform and Building Toolkit for Multi−Agent Intelligence
Yuhang Song‚ Andrzej Wojcicki‚ Thomas Lukasiewicz‚ Jianyi Wang‚ Abi Aryan‚ Zhenghua Xu‚ Mai Xu‚ Zihan Ding and Lianlong Wu
In Vincent Conitzer and Fei Sha, editors, Proceedings of the 34th National Conference on Artificial Intelligence‚ AAAI 2020‚ New York‚ New York‚ USA‚ February 7–12‚ 2020. AAAI Press. February, 2020.
Details about Arena: A General Evaluation Platform and Building Toolkit for Multi−Agent Intelligence | BibTeX data for Arena: A General Evaluation Platform and Building Toolkit for Multi−Agent Intelligence | Link to Arena: A General Evaluation Platform and Building Toolkit for Multi−Agent Intelligence
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[32]
Associative Memories in the Feature Space
Tommaso Salvatori‚ Beren Millidge‚ Yuhang Song‚ Rafal Bogacz and Thomas Lukasiewicz
In Proceedings of the 26th European Conference on Artificial Intelligence‚ ECAI 2023‚ Kraków‚ Poland‚ September 30 – October 5‚ 2023. IOS Press. September, 2023.
Details about Associative Memories in the Feature Space | BibTeX data for Associative Memories in the Feature Space
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[33]
Associative Memories via Predictive Coding
Tommaso Salvatori‚ Yuhang Song‚ Yujian Hong‚ Simon Frieder‚ Lei Sha‚ Zhenghua Xu‚ Rafal Bogacz and Thomas Lukasiewicz
In Proceedings of the 35th Annual Conference on Neural Information Processing Systems‚ NeurIPS 2021. December, 2021.
Details about Associative Memories via Predictive Coding | BibTeX data for Associative Memories via Predictive Coding | Link to Associative Memories via Predictive Coding
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[34]
BECEL: Benchmark for Consistency Evaluation of Language Models
Myeongjun Jang‚ Deuk Sin Kwon and Thomas Lukasiewicz
In Proceedings of the 29th International Conference on Computational Linguistics‚ COLING 2022‚ Gyeongju‚ Republic of Korea‚ October 2022. Pages 3680–3696. International Committee on Computational Linguistics. October, 2022.
Details about BECEL: Benchmark for Consistency Evaluation of Language Models | BibTeX data for BECEL: Benchmark for Consistency Evaluation of Language Models | Link to BECEL: Benchmark for Consistency Evaluation of Language Models
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[35]
Backpropagation at the Infinitesimal Inference Limit of Energy−Based Models: Unifying Predictive Coding‚ Equilibrium Propagation‚ and Contrastive Hebbian Learning
Beren Millidge‚ Yuhang Song‚ Tommaso Salvatori‚ Thomas Lukasiewicz and Rafal Bogacz
In Proceedings of the 11th International Conference on Learning Representations‚ ICLR 2023‚ Kigali‚ Rwanda‚ 1–5 May 2023. OpenReview.net. May, 2023.
Details about Backpropagation at the Infinitesimal Inference Limit of Energy−Based Models: Unifying Predictive Coding‚ Equilibrium Propagation‚ and Contrastive Hebbian Learning | BibTeX data for Backpropagation at the Infinitesimal Inference Limit of Energy−Based Models: Unifying Predictive Coding‚ Equilibrium Propagation‚ and Contrastive Hebbian Learning | Link to Backpropagation at the Infinitesimal Inference Limit of Energy−Based Models: Unifying Predictive Coding‚ Equilibrium Propagation‚ and Contrastive Hebbian Learning
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[36]
Basic Probabilistic Ontological Data Exchange with Existential Rules
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Livia Predoiu and Gerardo I. Simari
In Dale Schuurmans and Michael Wellman, editors, Proceedings of the 30th National Conference on Artificial Intelligence‚ AAAI 2016‚ Phoenix‚ Arizona‚ USA‚ February 12–17‚ 2016. Pages 1023−1029. AAAI Press. February, 2016.
Details about Basic Probabilistic Ontological Data Exchange with Existential Rules | BibTeX data for Basic Probabilistic Ontological Data Exchange with Existential Rules | Link to Basic Probabilistic Ontological Data Exchange with Existential Rules
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[37]
Beyond Distributional Hypothesis: Let Language Models Learn Meaning−Text Correspondence
Myeongjun Jang‚ Frank Martin Mtumbuka and Thomas Lukasiewicz
In Findings of NAACL 2022‚ Seattle‚ Washington‚ USA‚ July 2022. Pages 2030–2042. Association for Computational Linguistics. July, 2022.
Details about Beyond Distributional Hypothesis: Let Language Models Learn Meaning−Text Correspondence | BibTeX data for Beyond Distributional Hypothesis: Let Language Models Learn Meaning−Text Correspondence | Link to Beyond Distributional Hypothesis: Let Language Models Learn Meaning−Text Correspondence
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[38]
BoxE: A Box Embedding Model for Knowledge Base Completion
Ralph Abboud‚ İsmail İlkan Ceylan‚ Thomas Lukasiewicz and Tommaso Salvatori
In Proceedings of the 34th Annual Conference on Neural Information Processing Systems‚ NeurIPS 2020‚ December 6–12‚ 2020. December, 2020.
Details about BoxE: A Box Embedding Model for Knowledge Base Completion | BibTeX data for BoxE: A Box Embedding Model for Knowledge Base Completion | Link to BoxE: A Box Embedding Model for Knowledge Base Completion
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[39]
CCN+: A Neuro−symbolic Framework for Deep Learning with Requirements
Eleonora Giunchiglia‚ Alex Tatomir‚ Mihaela Catalina Stoian and Thomas Lukasiewicz
In International Journal of Approximate Reasoning. 2024.
In press.
Details about CCN+: A Neuro−symbolic Framework for Deep Learning with Requirements | BibTeX data for CCN+: A Neuro−symbolic Framework for Deep Learning with Requirements | Link to CCN+: A Neuro−symbolic Framework for Deep Learning with Requirements
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[40]
Can the Brain Do Backpropagation? — Exact Implementation of Backpropagation in Predictive Coding Networks
Yuhang Song‚ Thomas Lukasiewicz‚ Zhenghua Xu and Rafal Bogacz
In Proceedings of the 34th Annual Conference on Neural Information Processing Systems‚ NeurIPS 2020‚ December 6–12‚ 2020. December, 2020.
Details about Can the Brain Do Backpropagation? — Exact Implementation of Backpropagation in Predictive Coding Networks | BibTeX data for Can the Brain Do Backpropagation? — Exact Implementation of Backpropagation in Predictive Coding Networks | Link to Can the Brain Do Backpropagation? — Exact Implementation of Backpropagation in Predictive Coding Networks
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[41]
Can I Trust the Explainer? Verifying Post−hoc Explanatory Methods
Oana−Maria Camburu‚ Eleonora Giunchiglia‚ Jakob Foerster‚ Thomas Lukasiewicz and Phil Blunsom
2019.
Details about Can I Trust the Explainer? Verifying Post−hoc Explanatory Methods | BibTeX data for Can I Trust the Explainer? Verifying Post−hoc Explanatory Methods | Link to Can I Trust the Explainer? Verifying Post−hoc Explanatory Methods
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[42]
Causes and Explanations in the Structural−Model Approach : Tractable Cases
Thomas Eiter and Thomas Lukasiewicz
In Adnan Darwiche and Nir Friedman, editors, Proceedings of the 18th Conference on Uncertainty in Artificial Intelligence‚ UAI 2002‚ Edmonton‚ Alberta‚ Canada‚ August 1−4‚ 2002. Pages 146−153. Morgan Kaufmann. 2002.
Details about Causes and Explanations in the Structural−Model Approach : Tractable Cases | BibTeX data for Causes and Explanations in the Structural−Model Approach : Tractable Cases | Link to Causes and Explanations in the Structural−Model Approach : Tractable Cases
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[43]
Causes and Explanations in the Structural−Model Approach: Tractable Cases
Thomas Eiter and Thomas Lukasiewicz
In Artificial Intelligence. Vol. 170. No. 6/7. Pages 542–580. May, 2006.
Details about Causes and Explanations in the Structural−Model Approach: Tractable Cases | BibTeX data for Causes and Explanations in the Structural−Model Approach: Tractable Cases | Link to Causes and Explanations in the Structural−Model Approach: Tractable Cases
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[44]
Clustering Generative Adversarial Networks for Story Visualization
Bowen Li‚ Philip Torr and Thomas Lukasiewicz
In Proceedings of the 30th ACM Multimedia Conference‚ ACM MM 2022‚ Lisbon‚ Portugal‚ 10–14 October. Pages 769–778. ACM Press. October, 2022.
Details about Clustering Generative Adversarial Networks for Story Visualization | BibTeX data for Clustering Generative Adversarial Networks for Story Visualization | Link to Clustering Generative Adversarial Networks for Story Visualization
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[45]
Coherent Hierarchical Multi−Label Classification Networks
Eleonora Giunchiglia and Thomas Lukasiewicz
In Proceedings of the 34th Annual Conference on Neural Information Processing Systems‚ NeurIPS 2020‚ December 6–12‚ 2020. December, 2020.
Details about Coherent Hierarchical Multi−Label Classification Networks | BibTeX data for Coherent Hierarchical Multi−Label Classification Networks | Link to Coherent Hierarchical Multi−Label Classification Networks
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[46]
Collaborative Attention Guided Multi−Scale Feature Fusion Network for Medical Image Segmentation
Zhenghua Xu‚ Biao Tian‚ Shijie Liu‚ Xiangtao Wang‚ Di Yuan‚ Junhua Gu‚ Junyang Chen‚ Thomas Lukasiewicz and Victor C. M. Leung
In IEEE Transactions on Network Science and Engineering. Vol. 11. No. 2. Pages 1857–1871. 2023.
Details about Collaborative Attention Guided Multi−Scale Feature Fusion Network for Medical Image Segmentation | BibTeX data for Collaborative Attention Guided Multi−Scale Feature Fusion Network for Medical Image Segmentation | Link to Collaborative Attention Guided Multi−Scale Feature Fusion Network for Medical Image Segmentation
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[47]
Combining Answer Set Programming with Description Logics for the Semantic Web
Thomas Eiter‚ Thomas Lukasiewicz‚ Roman Schindlauer and Hans Tompits
In Didier Dubois‚ Christopher A. Welty and Mary−Anne Williams, editors, Proceedings of the 9th International Conference on the Principles of Knowledge Representation and Reasoning‚ KR 2004‚ Whistler‚ Canada‚ June 2−5‚ 2004. Pages 141−151. AAAI Press. 2004.
Details about Combining Answer Set Programming with Description Logics for the Semantic Web | BibTeX data for Combining Answer Set Programming with Description Logics for the Semantic Web | Link to Combining Answer Set Programming with Description Logics for the Semantic Web
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[48]
Combining Answer Set Programming with Description Logics for the Semantic Web
Thomas Eiter‚ Giovambattista Ianni‚ Thomas Lukasiewicz‚ Roman Schindlauer and Hans Tompits
In Artificial Intelligence. Vol. 172. No. 12/13. Pages 1495–1539. August, 2008.
AIJ Prominent Paper Award 2013
Details about Combining Answer Set Programming with Description Logics for the Semantic Web | BibTeX data for Combining Answer Set Programming with Description Logics for the Semantic Web | Link to Combining Answer Set Programming with Description Logics for the Semantic Web
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[49]
Combining Boolean Games with the Power of Ontologies for Automated Multi−Attribute Negotiation in the Semantic Web
Thomas Lukasiewicz and Azzurra Ragone
In Rubén Lara Hernandez‚ Tommaso Di Noia and Ioan Toma, editors, Proceedings of the 2nd International Workshop on Service Matchmaking and Resource Retrieval in the Semantic Web‚ SMRR 2008‚ Karlsruhe‚ Germany‚ October 27‚ 2008. Vol. 416 of CEUR Workshop Proceedings. CEUR−WS.org. 2008.
Details about Combining Boolean Games with the Power of Ontologies for Automated Multi−Attribute Negotiation in the Semantic Web | BibTeX data for Combining Boolean Games with the Power of Ontologies for Automated Multi−Attribute Negotiation in the Semantic Web | Download (pdf) of Combining Boolean Games with the Power of Ontologies for Automated Multi−Attribute Negotiation in the Semantic Web
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[50]
Combining Boolean Games with the Power of Ontologies for Automated Multi−attribute Negotiation in the Semantic Web
Thomas Lukasiewicz and Azzurra Ragone
In Proceedings of the 2009 IEEE/WIC/ACM International Conference on Intelligent Agent Technology‚ IAT 2009‚ Milan‚ Italy‚ 15−18 September 2009. Pages 395−402. IEEE Computer Society. 2009.
Details about Combining Boolean Games with the Power of Ontologies for Automated Multi−attribute Negotiation in the Semantic Web | BibTeX data for Combining Boolean Games with the Power of Ontologies for Automated Multi−attribute Negotiation in the Semantic Web | Link to Combining Boolean Games with the Power of Ontologies for Automated Multi−attribute Negotiation in the Semantic Web
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[51]
Combining CP−Nets with the Power of Ontologies
Tommaso Di Noia and Thomas Lukasiewicz
In Marie desJardins and Michael L. Littman, editors, Proceedings of the 27th AAAI Conference on Artificial Intelligence‚ AAAI 2013‚ Late Breaking Papers‚ Bellevue‚ Washington‚ USA‚ July 14−18‚ 2013. Vol. WS−13−17 of AAAI Workshops. AAAI Press. 2013.
Details about Combining CP−Nets with the Power of Ontologies | BibTeX data for Combining CP−Nets with the Power of Ontologies | Link to Combining CP−Nets with the Power of Ontologies
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[52]
Combining Existential Rules with the Power of CP−Theories
Tommaso Di Noia‚ Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Oana Tifrea−Marciuska
In Qiang Yang, editor, Proceedings of the 24th International Joint Conference on Artificial Intelligence‚ IJCAI 2015‚ Buenos Aires‚ Argentina‚ July 25−31‚ 2015. Pages 2918−2925. AAAI Press / International Joint Conferences on Artificial Intelligence. July, 2015.
Details about Combining Existential Rules with the Power of CP−Theories | BibTeX data for Combining Existential Rules with the Power of CP−Theories | Link to Combining Existential Rules with the Power of CP−Theories
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[53]
Combining Probabilistic Logic Programming with the Power of Maximum Entropy
Gabriele Kern−Isberner and Thomas Lukasiewicz
In Artificial Intelligence. Vol. 157. No. 1/2. Pages 139–202. August, 2004.
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[54]
Combining RDF and SPARQL with CP−Theories to Reason about Preferences in a Linked Data Setting
Jessica Rosati‚ Tommaso Di Noia‚ Renato De Leone‚ Thomas Lukasiewicz and Vito Walter Anelli
In Semantic Web. Vol. 11. No. 3. Pages 391–419. April, 2020.
Details about Combining RDF and SPARQL with CP−Theories to Reason about Preferences in a Linked Data Setting | BibTeX data for Combining RDF and SPARQL with CP−Theories to Reason about Preferences in a Linked Data Setting | Link to Combining RDF and SPARQL with CP−Theories to Reason about Preferences in a Linked Data Setting
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[55]
Combining Semantic Web Search with the Power of Inductive Reasoning
Claudia d'Amato‚ Nicola Fanizzi‚ Bettina Fazzinga‚ Georg Gottlob and Thomas Lukasiewicz
In Amol Deshpande and Anthony Hunter, editors, Proceedings of the 4th International Conference on Scalable Uncertainty Management‚ SUM 2010‚ Toulouse‚ France‚ September 27−29‚ 2010. Vol. 6379 of Lecture Notes in Computer Science. Pages 137−150. Springer. 2010.
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[56]
Combining Semantic Web Search with the Power of Inductive Reasoning
Claudia d'Amato‚ Nicola Fanizzi‚ Bettina Fazzinga‚ Georg Gottlob and Thomas Lukasiewicz
In Fernando Bobillo‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Trevor Martin‚ Matthias Nickles‚ Michael Pool and Pavel Smrz, editors, Proceedings of the 5th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2009‚ Washington DC‚ USA‚ October 26‚ 2009. Vol. 527 of CEUR Workshop Proceedings. Pages 15−26. CEUR−WS.org. 2009.
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[57]
Complexity Results for Default Reasoning from Conditional Knowledge Bases
Thomas Eiter and Thomas Lukasiewicz
In Anthony G. Cohn‚ Fausto Giunchiglia and Bart Selman, editors, Proceedings of the 7th International Conference on the Principles of Knowledge Representation and Reasoning‚ KR 2000‚ Breckenridge‚ Colorado‚ USA‚ April 11−15‚ 2000. Pages 62−73. Morgan Kaufmann. 2000.
Details about Complexity Results for Default Reasoning from Conditional Knowledge Bases | BibTeX data for Complexity Results for Default Reasoning from Conditional Knowledge Bases | Link to Complexity Results for Default Reasoning from Conditional Knowledge Bases
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[58]
Complexity Results for Explanations in the Structural−Model Approach
Thomas Eiter and Thomas Lukasiewicz
In Dieter Fensel‚ Fausto Giunchiglia‚ Deborah L. McGuinness and Mary−Anne Williams, editors, Proceedings of the 8th International Conference on Principles and Knowledge Representation and Reasoning‚ KR 2002‚ Toulouse‚ France‚ April 22−25‚ 2002. Pages 49−60. Morgan Kaufmann. 2002.
Details about Complexity Results for Explanations in the Structural−Model Approach | BibTeX data for Complexity Results for Explanations in the Structural−Model Approach | Download (pdf) of Complexity Results for Explanations in the Structural−Model Approach
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[59]
Complexity Results for Explanations in the Structural−Model Approach
Thomas Eiter and Thomas Lukasiewicz
In Artificial Intelligence. Vol. 154. No. 1/2. Pages 145–198. April, 2004.
Details about Complexity Results for Explanations in the Structural−Model Approach | BibTeX data for Complexity Results for Explanations in the Structural−Model Approach | Link to Complexity Results for Explanations in the Structural−Model Approach
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[60]
Complexity Results for Preference Aggregation over (m)CP−Nets: Max and Rank Voting
Thomas Lukasiewicz and Enrico Malizia
In Artificial Intelligence. Vol. 303. Pages 103636. February, 2022.
Details about Complexity Results for Preference Aggregation over (m)CP−Nets: Max and Rank Voting | BibTeX data for Complexity Results for Preference Aggregation over (m)CP−Nets: Max and Rank Voting | Link to Complexity Results for Preference Aggregation over (m)CP−Nets: Max and Rank Voting
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[61]
Complexity Results for Preference Aggregation over (m)CP−nets: Pareto and Majority Voting
Thomas Lukasiewicz and Enrico Malizia
In Artificial Intelligence. Vol. 272. Pages 101–142. July, 2019.
Details about Complexity Results for Preference Aggregation over (m)CP−nets: Pareto and Majority Voting | BibTeX data for Complexity Results for Preference Aggregation over (m)CP−nets: Pareto and Majority Voting | Link to Complexity Results for Preference Aggregation over (m)CP−nets: Pareto and Majority Voting
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[62]
Complexity Results for Probabilistic Datalog+⁄−
İsmail İlkan Ceylan‚ Thomas Lukasiewicz and Rafael Peñaloza
In Maria S. Fox and Gal A. Kaminka, editors, Proceedings of the 22nd European Conference on Artificial Intelligence‚ ECAI 2016‚ The Hague‚ The Netherlands‚ August 29 − September 2‚ 2016. Pages 1414−1422. IOS Press. August, 2016.
Details about Complexity Results for Probabilistic Datalog+⁄− | BibTeX data for Complexity Results for Probabilistic Datalog+⁄− | Link to Complexity Results for Probabilistic Datalog+⁄−
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[63]
Complexity Results for Structure−Based Causality
Thomas Eiter and Thomas Lukasiewicz
In Bernhard Nebel, editor, Proceedings of the 17th International Joint Conference on Artificial Intelligence‚ IJCAI 2001‚ Seattle‚ Washington‚ USA‚ August 4−10‚ 2001. Pages 35−42. Morgan Kaufmann. 2001.
IJCAI−01 Distinguished Paper Award (best paper of 796 submitted and 197 accepted papers at IJCAI−01).
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[64]
Complexity Results for Structure−Based Causality
Thomas Eiter and Thomas Lukasiewicz
In Artificial Intelligence. Vol. 142. No. 1. Pages 53–89. November, 2002.
Details about Complexity Results for Structure−Based Causality | BibTeX data for Complexity Results for Structure−Based Causality | Link to Complexity Results for Structure−Based Causality
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[65]
Complexity of Approximate Query Answering under Inconsistency in Datalog+⁄−
Thomas Lukasiewicz‚ Enrico Malizia and Cristian Molinaro
In Sonia Bergamaschi‚ Tommaso Di Noia and Andrea Maurino, editors, Proceedings of the 26th Italian Symposium on Advanced Database Systems‚ Castellaneta Marina (Taranto)‚ Italy‚ June 24−27‚ 2018. Vol. 2161 of CEUR Workshop Proceedings. CEUR−WS.org. 2018.
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[66]
Complexity of Approximate Query Answering under Inconsistency in Datalog+⁄−
Thomas Lukasiewicz‚ Enrico Malizia and Cristian Molinaro
In Jérôme Lang, editor, Proceedings of the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence‚ IJCAI−ECAI 2018‚ Stockholm‚ Sweden‚ July 13−19‚ 2018. Pages 1921−1927. IJCAI/AAAI Press. July, 2018.
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[67]
Complexity of Inconsistency−Tolerant Query Answering in Datalog+/ under Cardinality−Based Repairs
Thomas Lukasiewicz‚ Enrico Malizia and Andrius Vaicenavicius
In Giuseppe Amato‚ Valentina Bartalesi‚ Devis Bianchini‚ Claudio Gennaro and Riccardo Torlone, editors, Proceedings of the 30th Italian Symposium on Advanced Database Systems‚ SEBD 2022‚ Tirrenia (PI)‚ Italy‚ June 19−22‚ 2022. Vol. 3194 of CEUR Workshop Proceedings. Pages 530–537. CEUR−WS.org. 2022.
Details about Complexity of Inconsistency−Tolerant Query Answering in Datalog+/ under Cardinality−Based Repairs | BibTeX data for Complexity of Inconsistency−Tolerant Query Answering in Datalog+/ under Cardinality−Based Repairs | Download (pdf) of Complexity of Inconsistency−Tolerant Query Answering in Datalog+/ under Cardinality−Based Repairs
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[68]
Complexity of Inconsistency−Tolerant Query Answering in Datalog+/ under Preferred Repairs
Thomas Lukasiewicz‚ Enrico Malizia and Cristian Molinaro
In Pierre Marquis and Tran Cao Son, editors, Proceedings of 20th International Conference on Principles of Knowledge Representation and Reasoning‚ KR 2023‚ Rhodes‚ Greece‚ September 2−8‚ 2023. AAAI Press. September, 2023.
Details about Complexity of Inconsistency−Tolerant Query Answering in Datalog+/ under Preferred Repairs | BibTeX data for Complexity of Inconsistency−Tolerant Query Answering in Datalog+/ under Preferred Repairs
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[69]
Complexity of Inconsistency−Tolerant Query Answering in Datalog+⁄−
Thomas Lukasiewicz‚ Maria Vanina Martinez and Gerardo I. Simari
In Thomas Eiter‚ Birte Glimm‚ Yevgeny Kazakov and Markus Krötzsch, editors, Proceedings of the 26th International Workshop on Description Logics‚ DL 2013‚ Ulm‚ Germany‚ July 23−26‚ 2013. Vol. 1014 of CEUR Workshop Proceedings. Pages 791−803. CEUR−WS.org. 2013.
Details about Complexity of Inconsistency−Tolerant Query Answering in Datalog+⁄− | BibTeX data for Complexity of Inconsistency−Tolerant Query Answering in Datalog+⁄− | Download (pdf) of Complexity of Inconsistency−Tolerant Query Answering in Datalog+⁄−
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[70]
Complexity of Inconsistency−Tolerant Query Answering in Datalog+⁄−
Thomas Lukasiewicz‚ Maria Vanina Martinez and Gerardo I. Simari
In Robert Meersman‚ Hervé Panetto‚ Tharam Dillon‚ Johann Eder‚ Zohra Bellahsene‚ Norbert Ritter‚ Pieter De Leenheer and Deijing Dou, editors, Proceedings of the 12th International Conference on Ontologies‚ Databases‚ and Applications of Semantics‚ ODBASE 2013‚ Graz‚ Austria‚ September 10−11‚ 2013. Vol. 8185 of Lecture Notes in Computer Science. Pages 488−500. Springer. 2013.
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[71]
Complexity of Inconsistency−Tolerant Query Answering in Datalog+⁄− under Cardinality−Based Repairs
Thomas Lukasiewicz‚ Enrico Malizia and Andrius Vaicenavičius
In Pascal Van Hentenryck and Zhi−Hua Zhou, editors, Proceedings of the 33rd National Conference on Artificial Intelligence‚ AAAI 2019‚ Honolulu‚ Hawaii‚ USA‚ January 27 − February 1‚ 2019. Pages 2962–2969. AAAI Press. January, 2019.
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[72]
Complexity of Threshold Query Answering in Probabilistic Ontological Data Exchange
Thomas Lukasiewicz and Livia Predoiu
In Maria S. Fox and Gal A. Kaminka, editors, Proceedings of the 22nd European Conference on Artificial Intelligence‚ ECAI 2016‚ The Hague‚ The Netherlands‚ August 29 − September 2‚ 2016. Pages 1008−1016. IOS Press. August, 2016.
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[73]
Computing k−Rank Answers with Ontological CP−Nets
Tommaso Di Noia‚ Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Oana Tifrea−Marciuska
In Sergio Greco and Antonio Picariello, editors, Proceedings of the 22nd Italian Symposium on Advanced Database Systems‚ SEBD 2014‚ Sorrento Coast‚ Italy‚ June 16−18‚ 2014. 2014.
Details about Computing k−Rank Answers with Ontological CP−Nets | BibTeX data for Computing k−Rank Answers with Ontological CP−Nets
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[74]
Computing k−Rank Answers with Ontological CP−Nets
Tommaso Di Noia‚ Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Oana Tifrea−Marciuska
In Thomas Lukasiewicz‚ Rafael Peñaloza and Anni−Yasmin Turhan, editors, Proceedings of the 1st Workshop on Logics for Reasoning about Preferences‚ Uncertainty‚ and Vagueness‚ PRUV 2014‚ Vienna‚ Austria‚ July 23−24‚ 2014. Vol. 1205 of CEUR Workshop Proceedings. Pages 74−87. CEUR−WS.org. 2014.
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[75]
Computing k−Rank Answers with Ontological CP−Nets
Tommaso Di Noia‚ Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Oana Tifrea−Marciuska
No. RR−14−03. DCS. 2014.
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[76]
Conjunctive Query Answering in Probabilistic Datalog+⁄− Ontologies
Georg Gottlob‚ Thomas Lukasiewicz and Gerardo I. Simari
In Sebastian Rudolph and Claudio Gutierrez, editors, Proceedings of the 5th International Conference on Web Reasoning and Rule Systems‚ RR 2011‚ Galway‚ Ireland‚ August 29−30‚ 2011. Vol. 6902 of Lecture Notes in Computer Science. Pages 77−92. Springer. 2011.
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[77]
Consistency Analysis of ChatGPT
Myeongjun Erik Jang and Thomas Lukasiewicz
In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing‚ EMNLP 2023‚ Singapore‚ December 6−10‚ 2023. Association for Computational Linguistics. December, 2023.
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[78]
Consistent Answers in Probabilistic Datalog+⁄− Ontologies
Thomas Lukasiewicz‚ Maria Vanina Martinez and Gerardo I. Simari
In Markus Krötzsch and Umberto Straccia, editors, Proceedings of the 6th International Conference on Web Reasoning and Rule Systems‚ RR 2012‚ Vienna‚ Austria‚ September 10−12‚ 2012. Vol. 7497 of Lecture Notes in Computer Science. Pages 156−171. Springer. 2012.
Details about Consistent Answers in Probabilistic Datalog+⁄− Ontologies | BibTeX data for Consistent Answers in Probabilistic Datalog+⁄− Ontologies | Link to Consistent Answers in Probabilistic Datalog+⁄− Ontologies
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[79]
Controllable Text−to−Image Generation
Bowen Li‚ Xiaojuan Qi‚ Thomas Lukasiewicz and Philip H. S. Torr
In Proceedings of the 33rd Annual Conference on Neural Information Processing Systems‚ NeurIPS 2019‚ Vancouver‚ Canada‚ December 8–14‚ 2019. December, 2019.
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[80]
Controlling Text Edition by Changing Answers of Specific Questions
Lei Sha‚ Patrick Hohenecker and Thomas Lukasiewicz
In Findings of ACL. 2021.
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[81]
Correcting Flaws in Common Disentanglement Metrics
Louis Mahon‚ Lei Sha and Thomas Lukasiewicz
In Transactions on Machine Learning Research. 2024.
In press.
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[82]
Counter−GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns
Zhongbin Xie‚ Vid Kocijan‚ Thomas Lukasiewicz and Oana−Maria Camburu
In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics‚ EACL 2023‚ Dubrovnik‚ Croatia‚ 2–6 May 2023. Pages 3761–3773. Association for Computational Linguistics. May, 2023.
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[83]
Credal Networks under Maximum Entropy
Thomas Lukasiewicz
In Craig Boutilier and Moisés Goldszmidt, editors, Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence‚ UAI 2000‚ Stanford‚ California‚ USA‚ June 30 − July 3‚ 2000. Pages 363−370. Morgan Kaufmann. 2000.
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[84]
Datalog+⁄−: A Family of Languages for Ontology Querying
Andrea Calì‚ Georg Gottlob‚ Thomas Lukasiewicz and Andreas Pieris
In Oege de Moor‚ Georg Gottlob‚ Tim Furche and Andrew Jon Sellers, editors, Datalog Reloaded − 1st International Workshop‚ Datalog 2010‚ Oxford‚ UK‚ March 16−19‚ 2010. Revised Selected Papers. Vol. 6702 of Lecture Notes in Computer Science. Pages 351−368. Springer. 2011.
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[85]
Datalog+⁄−: A Family of Logical Knowledge Representation and Query Languages for New Applications
Andrea Calì‚ Georg Gottlob‚ Thomas Lukasiewicz‚ Bruno Marnette and Andreas Pieris
In Proceedings of the 25th IEEE Symposium on Logic in Computer Science‚ LICS 2010‚ Edinburgh‚ UK‚ July 2010. Pages 228–242. IEEE Computer Society. 2010.
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[86]
Datalog+⁄−: Questions and Answers
Georg Gottlob‚ Thomas Lukasiewicz and Andreas Pieris
In Chitta Baral and Giuseppe De Giacomo, editors, Proceedings of the 14th International Conference on the Principles of Knowledge Representation and Reasoning‚ KR 2014‚ Vienna‚ Austria‚ July 20−24‚ 2014. Pages 682−685. AAAI Press. 2014.
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[87]
Datalog±: A Unified Approach to Ontologies and Integrity Constraints
Andrea Calì‚ Georg Gottlob and Thomas Lukasiewicz
In Ronald Fagin, editor, Proceedings of the 12th International Conference on Database Theory‚ ICDT 2009‚ St. Petersburg‚ Russia‚ March 23−25‚ 2009. Vol. 361 of ACM International Conference Proceeding Series. Pages 14−30. ACM Press. 2009.
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[88]
Deep Bayesian Gaussian Processes for Uncertainty Estimation in Electronic Health Records
Yikuan Li‚ Shishir Rao‚ Abdelaali Hassaine‚ Rema Ramakrishnan‚ Dexter Canoy‚ Gholamreza Salimi−Khorshidi‚ Mohammad Mamouei‚ Thomas Lukasiewicz and Kazem Rahimi
In Scientific Reports. Vol. 11. Pages 20685:1–13. October, 2021.
Details about Deep Bayesian Gaussian Processes for Uncertainty Estimation in Electronic Health Records | BibTeX data for Deep Bayesian Gaussian Processes for Uncertainty Estimation in Electronic Health Records | Link to Deep Bayesian Gaussian Processes for Uncertainty Estimation in Electronic Health Records
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[89]
Deep Learning for Ontology Reasoning
Patrick Hohenecker and Thomas Lukasiewicz
2017.
Details about Deep Learning for Ontology Reasoning | BibTeX data for Deep Learning for Ontology Reasoning | Link to Deep Learning for Ontology Reasoning
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[90]
Deep Learning with Logical Constraints
Eleonora Giunchiglia‚ Mihaela Catalina Stoian and Thomas Lukasiewicz
In Luc De Raedt, editor, Proceedings of the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence‚ IJCAI−ECAI 2022‚ Survey Track‚ Vienna‚ Austria‚ July 23−29‚ 2022. Pages 5478–5485. IJCAI/AAAI Press. July, 2022.
Details about Deep Learning with Logical Constraints | BibTeX data for Deep Learning with Logical Constraints | Link to Deep Learning with Logical Constraints
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[91]
Default Reasoning from Conditional Knowledge Bases: Complexity and Tractable Cases
Thomas Eiter and Thomas Lukasiewicz
In Artificial Intelligence. Vol. 124. No. 2. Pages 169–241. December, 2000.
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[92]
Democratizing Financial Knowledge Graph Construction by Mining Massive Brokerage Research Reports
Zehua Cheng‚ Lianlong Wu‚ Thomas Lukasiewicz‚ Emanuel Sallinger and Georg Gottlob
In Maya Ramanath and Themis Palpanas, editors, Proceedings of the Workshops of the EDBT/ICDT 2022 Joint Conference‚ Edinburgh‚ UK‚ March 29‚ 2022. Vol. 3135 of CEUR Workshop Proceedings. CEUR−WS.org. 2022.
Details about Democratizing Financial Knowledge Graph Construction by Mining Massive Brokerage Research Reports | BibTeX data for Democratizing Financial Knowledge Graph Construction by Mining Massive Brokerage Research Reports | Download (pdf) of Democratizing Financial Knowledge Graph Construction by Mining Massive Brokerage Research Reports
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[93]
Description Logic Programs Under Probabilistic Uncertainty and Fuzzy Vagueness
Thomas Lukasiewicz and Umberto Straccia
In Khaled Mellouli, editor, Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty‚ ECSQARU 2007‚ Hammamet‚ Tunisia‚ October 31 − November 2‚ 2007. Vol. 4724 of Lecture Notes in Computer Science. Pages 187−198. Springer. 2007.
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[94]
Description Logic Programs under Probabilistic Uncertainty and Fuzzy Vagueness
Thomas Lukasiewicz and Umberto Straccia
In International Journal of Approximate Reasoning. Vol. 50. No. 6. Pages 837–853. June, 2009.
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[95]
Diversity−Driven Extensible Hierarchical Reinforcement Learning
Yuhang Song‚ Jianyi Wang‚ Thomas Lukasiewicz‚ Zhenghua Xu and Mai Xu
In Pascal Van Hentenryck and Zhi−Hua Zhou, editors, Proceedings of the 33rd National Conference on Artificial Intelligence‚ AAAI 2019‚ Honolulu‚ Hawaii‚ USA‚ January 27 − February 1‚ 2019. Pages 4992–4999. AAAI Press. January, 2019.
Details about Diversity−Driven Extensible Hierarchical Reinforcement Learning | BibTeX data for Diversity−Driven Extensible Hierarchical Reinforcement Learning | Link to Diversity−Driven Extensible Hierarchical Reinforcement Learning
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[96]
Does the Objective Matter? Comparing Training Objectives for Pronoun Resolution
Yordan Yordanov‚ Oana−Maria Camburu‚ Vid Kocijan and Thomas Lukasiewicz
In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing‚ EMNLP 2020‚ November 16–20‚ 2020. Pages 4963–4969. Association for Computational Linguistics. November, 2020.
Details about Does the Objective Matter? Comparing Training Objectives for Pronoun Resolution | BibTeX data for Does the Objective Matter? Comparing Training Objectives for Pronoun Resolution | Link to Does the Objective Matter? Comparing Training Objectives for Pronoun Resolution
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[97]
EFPN: Effective medical image detection using feature pyramid fusion enhancement
Zhenghua Xu‚ Xudong Zhang‚ Hexiang Zhang‚ Yunxin Liu‚ Yuefu Zhan and Thomas Lukasiewicz
In Computers in Biology and Medicine. Vol. 163. Pages 107149. 2023.
Details about EFPN: Effective medical image detection using feature pyramid fusion enhancement | BibTeX data for EFPN: Effective medical image detection using feature pyramid fusion enhancement | Link to EFPN: Effective medical image detection using feature pyramid fusion enhancement
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[98]
Efficient Deep Clustering of Human Activities and How to Improve Evaluation
Louis Mahon and Thomas Lukasiewicz
In Emtiyaz Khan and Mehmet Gonen, editors, Proceedings of the 14th Asian Conference on Machine Learning‚ ACML 2022‚ Hyderabad‚ India‚ 12–14 December 2022. Vol. 189 of Proceedings of Machine Learning Research. Pages 722–737. PMLR. December, 2022.
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[99]
Efficient Global Probabilistic Deduction from Taxonomic and Probabilistic Knowledge−Bases over Conjunctive Events
Thomas Lukasiewicz
In Forouzan Golshani and Kia Makki, editors, Proceedings of the 6th International Conference on Information and Knowledge Management‚ CIKM 1997‚ Las Vegas‚ Nevada‚ November 10−14‚ 1997. Pages 75−82. ACM Press. 1997.
Details about Efficient Global Probabilistic Deduction from Taxonomic and Probabilistic Knowledge−Bases over Conjunctive Events | BibTeX data for Efficient Global Probabilistic Deduction from Taxonomic and Probabilistic Knowledge−Bases over Conjunctive Events | Link to Efficient Global Probabilistic Deduction from Taxonomic and Probabilistic Knowledge−Bases over Conjunctive Events
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[100]
Equality−Friendly Well−Founded Semantics and Applications to Description Logics
Georg Gottlob‚ André Hernich‚ Clemens Kupke and Thomas Lukasiewicz
In Yevgeny Kazakov‚ Domenico Lembo and Frank Wolter, editors, Proceedings of the 25th International Workshop on Description Logics‚ DL 2012‚ Rome‚ Italy‚ June 7−10‚ 2012. Vol. 846 of CEUR Workshop Proceedings. CEUR−WS.org. 2012.
Details about Equality−Friendly Well−Founded Semantics and Applications to Description Logics | BibTeX data for Equality−Friendly Well−Founded Semantics and Applications to Description Logics | Download (pdf) of Equality−Friendly Well−Founded Semantics and Applications to Description Logics
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[101]
Equality−Friendly Well−Founded Semantics and Applications to Description Logics
Georg Gottlob‚ André Hernich‚ Clemens Kupke and Thomas Lukasiewicz
In J. Hoffmann and B. Selman, editors, Proceedings of the 26th National Conference on Artificial Intelligence‚ AAAI 2012‚ Toronto‚ Ontario‚ Canada‚ July 2012. AAAI Press. 2012.
Details about Equality−Friendly Well−Founded Semantics and Applications to Description Logics | BibTeX data for Equality−Friendly Well−Founded Semantics and Applications to Description Logics | Link to Equality−Friendly Well−Founded Semantics and Applications to Description Logics
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[102]
Evaluating Language Models for Mathematics through Interactions
Katherine M. Collins‚ Albert Jiang‚ Simon Frieder‚ Lionel Wong‚ Miri Zilka‚ Umang Bhatt‚ Thomas Lukasiewicz‚ Yuhuai Wu‚ Joshua B. Tenenbaum‚ William Hart‚ Timothy Gowers‚ Wenda Li‚ Adrian Weller and Mateja Jamnik
In Proceedings of the National Academy of Sciences of the United States of America (PNAS). Vol. 121. No. 24. June, 2024.
Details about Evaluating Language Models for Mathematics through Interactions | BibTeX data for Evaluating Language Models for Mathematics through Interactions | Link to Evaluating Language Models for Mathematics through Interactions
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[103]
Existential Rules and Bayesian Networks for Probabilistic Ontological Data Exchange
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Livia Predoiu and Gerardo I. Simari
In Nick Bassiliades‚ Georg Gottlob and Fariba Sadri, editors, Proceedings of the 9th International Web Rule Symposium‚ RuleML 2015‚ Berlin‚ Germany‚ August 2−5‚ 2015.. Vol. 9202 of Lecture Notes in Computer Science. Pages 294−310. Springer. 2015.
RuleML 2015 Best Paper Award
Details about Existential Rules and Bayesian Networks for Probabilistic Ontological Data Exchange | BibTeX data for Existential Rules and Bayesian Networks for Probabilistic Ontological Data Exchange | Link to Existential Rules and Bayesian Networks for Probabilistic Ontological Data Exchange
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[104]
Explaining Chest X−ray Pathologies in Natural Language
Maxime Kayser‚ Cornelius Emde‚ Oana Camburu‚ Guy Parsons‚ Bartlomiej Papiez and Thomas Lukasiewicz
In Linwei Wang‚ Qi Dou‚ P. Thomas Fletcher‚ Stefanie Speidel and Shuo Li, editors, Proceedings of the 25th International Conference on Medical Image Computing and Computer−Assisted Intervention‚ MICCAI 2022‚ Singapore‚ 18–22 September 2022. Vol. 13435 of Lecture Notes in Computer Science (LNCS). Pages 701–713. Springer. September, 2022.
Details about Explaining Chest X−ray Pathologies in Natural Language | BibTeX data for Explaining Chest X−ray Pathologies in Natural Language | Link to Explaining Chest X−ray Pathologies in Natural Language
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[105]
Explanations for Inconsistency−Tolerant Query Answering under Existential Rules
Thomas Lukasiewicz‚ Enrico Malizia and Cristian Molinaro
In Giuseppe Amato‚ Valentina Bartalesi‚ Devis Bianchini‚ Claudio Gennaro and Riccardo Torlone, editors, Proceedings of the 30th Italian Symposium on Advanced Database Systems‚ SEBD 2022‚ Tirrenia (PI)‚ Italy‚ June 19−22‚ 2022. Vol. 3194 of CEUR Workshop Proceedings. Pages 489–496. CEUR−WS.org. 2022.
Details about Explanations for Inconsistency−Tolerant Query Answering under Existential Rules | BibTeX data for Explanations for Inconsistency−Tolerant Query Answering under Existential Rules | Download (pdf) of Explanations for Inconsistency−Tolerant Query Answering under Existential Rules
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[106]
Explanations for Inconsistency−Tolerant Query Answering under Existential Rules
Thomas Lukasiewicz‚ Enrico Malizia and Cristian Molinaro
In Vincent Conitzer and Fei Sha, editors, Proceedings of the 34th National Conference on Artificial Intelligence‚ AAAI 2020‚ New York‚ New York‚ USA‚ February 7–12‚ 2020. AAAI Press. February, 2020.
Details about Explanations for Inconsistency−Tolerant Query Answering under Existential Rules | BibTeX data for Explanations for Inconsistency−Tolerant Query Answering under Existential Rules | Link to Explanations for Inconsistency−Tolerant Query Answering under Existential Rules
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[107]
Explanations for Negative Query Answers under Existential Rules
İsmail İlkan Ceylan‚ Thomas Lukasiewicz‚ Enrico Malizia‚ Cristian Molinaro and Andrius Vaicenavičius
In Diego Calvanese and Esra Erdem, editors, Proceedings of 17th International Conference on Principles of Knowledge Representation and Reasoning‚ KR 2020‚ Rhodes‚ Greece‚ September 12−18‚ 2020. AAAI Press. September, 2020.
Details about Explanations for Negative Query Answers under Existential Rules | BibTeX data for Explanations for Negative Query Answers under Existential Rules | Link to Explanations for Negative Query Answers under Existential Rules
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[108]
Explanations for Negative Query Answers under Inconsistency−Tolerant Semantics
Thomas Lukasiewicz‚ Enrico Malizia and Cristian Molinaro
In Luc De Raedt, editor, Proceedings of the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence‚ IJCAI−ECAI 2022‚ Vienna‚ Austria‚ July 23−29‚ 2022. Pages 2705–2711. IJCAI/AAAI Press. July, 2022.
Details about Explanations for Negative Query Answers under Inconsistency−Tolerant Semantics | BibTeX data for Explanations for Negative Query Answers under Inconsistency−Tolerant Semantics | Link to Explanations for Negative Query Answers under Inconsistency−Tolerant Semantics
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[109]
Explanations for Ontology−Mediated Query Answering in Description Logics
İsmail İlkan Ceylan‚ Thomas Lukasiewicz‚ Enrico Malizia and Andrius Vaicenavičius
In Giuseppe De Giacomo, editor, Proceedings of the 24th European Conference on Artificial Intelligence‚ ECAI 2020‚ Santiago de Compostela‚ Spain‚ June 8–12‚ 2020. IOS Press. June, 2020.
Details about Explanations for Ontology−Mediated Query Answering in Description Logics | BibTeX data for Explanations for Ontology−Mediated Query Answering in Description Logics | Link to Explanations for Ontology−Mediated Query Answering in Description Logics
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[110]
Explanations for Ontology−Mediated Query Answering in Description Logics (Extended Abstract)
İsmail İlkan Ceylan‚ Thomas Lukasiewicz‚ Enrico Malizia and Andrius Vaicenavicius
In Stefan Borgwardt and Thomas Meyer, editors, Proceedings of the 33rd International Workshop on Description Logics‚ DL 2020‚ co−located with the 17th International Conference on Principles of Knowledge Representation and Reasoning‚ KR 2020‚ Online Event [Rhodes‚ Greece]‚ September 12–14‚ 2020. Vol. 2663 of CEUR Workshop Proceedings. CEUR−WS.org. 2020.
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[111]
Explanations for Query Answers under Existential Rules
İsmail İlkan Ceylan‚ Thomas Lukasiewicz‚ Enrico Malizia and Andrius Vaicenavičius
In Artificial Intelligence. 2024.
Conditionally accepted for publication
Details about Explanations for Query Answers under Existential Rules | BibTeX data for Explanations for Query Answers under Existential Rules
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[112]
Explanations for Query Answers under Existential Rules
İsmail İlkan Ceylan‚ Thomas Lukasiewicz‚ Enrico Malizia and Andrius Vaicenavičius
In Sarit Kraus, editor, Proceedings of the 28th International Joint Conference on Artificial Intelligence‚ IJCAI 2019‚ Macao‚ China‚ August 10−16‚ 2019. Pages 1639–1646. IJCAI/AAAI Press. August, 2019.
Details about Explanations for Query Answers under Existential Rules | BibTeX data for Explanations for Query Answers under Existential Rules | Download (pdf) of Explanations for Query Answers under Existential Rules | Link to Explanations for Query Answers under Existential Rules
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[113]
Exploiting T−norms for Deep Learning in Autonomous Driving
Mihaela Catalina Stoian‚ Eleonora Giunchiglia and Thomas Lukasiewicz
In Artur S. d'Avila Garcez‚ Tarek R. Besold‚ Marco Gori and Ernesto Jiménez−Ruiz, editors, Proceedings of the 17th International Workshop on Neural−Symbolic Learning and Reasoning‚ NeSy 2023‚ La Certosa di Pontignano‚ Siena‚ Italy‚ 3–5 July 2023. Pages 369–380. July, 2023.
Details about Exploiting T−norms for Deep Learning in Autonomous Driving | BibTeX data for Exploiting T−norms for Deep Learning in Autonomous Driving
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[114]
Expressive Probabilistic Description Logics
Thomas Lukasiewicz
In Artificial Intelligence. Vol. 172. No. 6/7. Pages 852–883. April, 2008.
Details about Expressive Probabilistic Description Logics | BibTeX data for Expressive Probabilistic Description Logics | Link to Expressive Probabilistic Description Logics
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[115]
Extension of the Relational Algebra to Probabilistic Complex Values
Thomas Eiter‚ Thomas Lukasiewicz and Michael Walter
In Klaus−Dieter Schewe and Bernhard Thalheim, editors, Proceedings of the 1st International Symposium on the Foundations of Information and Knowledge Systems‚ FoIKS 2000‚ Burg‚ Germany‚ February 14−17‚ 2000. Vol. 1762 of Lecture Notes in Computer Science. Pages 94−115. Springer. 2000.
Details about Extension of the Relational Algebra to Probabilistic Complex Values | BibTeX data for Extension of the Relational Algebra to Probabilistic Complex Values | Link to Extension of the Relational Algebra to Probabilistic Complex Values
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[116]
Extracting Outcomes from Appellate Decisions in US State Courts
Alina Petrova‚ John Armour and Thomas Lukasiewicz
In Serena Villata, editor, Proceedings of the 33rd International Conference on Legal Knowledge and Information Systems‚ JURIX 2020‚ Online‚ December 9–11‚ 2020.. Vol. 334. Pages 133–142. IOS Press. 2020.
Details about Extracting Outcomes from Appellate Decisions in US State Courts | BibTeX data for Extracting Outcomes from Appellate Decisions in US State Courts | Link to Extracting Outcomes from Appellate Decisions in US State Courts
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[117]
Faithfulness Tests for Natural Language Explanations
Pepa Atanasova‚ Oana−Maria Camburu‚ Christina Lioma‚ Thomas Lukasiewicz‚ Jakob Grue Simonsen and Isabelle Augenstein
In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics‚ ACL 2023‚ Toronto‚ Canada‚ July 9–14‚ 2023. Association for Computational Linguistics. July, 2023.
Details about Faithfulness Tests for Natural Language Explanations | BibTeX data for Faithfulness Tests for Natural Language Explanations
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[118]
Few−Shot Out−of−Domain Transfer Learning of Natural Language Explanations in a Label−Abundant Setup
Yordan Yordanov‚ Vid Kocijan‚ Thomas Lukasiewicz and Oana−Maria Camburu
In Findings of EMNLP 2022. Pages 3486–3501. Association for Computational Linguistics. December, 2022.
Details about Few−Shot Out−of−Domain Transfer Learning of Natural Language Explanations in a Label−Abundant Setup | BibTeX data for Few−Shot Out−of−Domain Transfer Learning of Natural Language Explanations in a Label−Abundant Setup | Link to Few−Shot Out−of−Domain Transfer Learning of Natural Language Explanations in a Label−Abundant Setup
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[119]
Fixpoint Characterizations for Many−Valued Disjunctive Logic Programs with Probabilistic Semantics
Thomas Lukasiewicz
In Thomas Eiter‚ Wolfgang Faber and Miroslaw Truszczynski, editors, Proceedings of the 6th International Conference on Logic Programming and Nonmonotonic Reasoning‚ LPNMR 2001‚ Vienna‚ Austria‚ September 17−19‚ 2001. Vol. 2173 of Lecture Notes in Computer Science. Pages 336−350. Springer. 2001.
Details about Fixpoint Characterizations for Many−Valued Disjunctive Logic Programs with Probabilistic Semantics | BibTeX data for Fixpoint Characterizations for Many−Valued Disjunctive Logic Programs with Probabilistic Semantics | Link to Fixpoint Characterizations for Many−Valued Disjunctive Logic Programs with Probabilistic Semantics
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[120]
Fool Me Once? Contrasting Vision− and Language−based Explanations in a Clinical Decision−Support Setting
Maxime Kayser‚ Bayar Menzat‚ Cornelius Emde‚ Bogdan Bercean‚ Bartlomiej W. Papiez‚ Alex Novak‚ Abdala Espinosa‚ Susanne Gaube‚ Thomas Lukasiewicz and Oana−Maria Camburu
In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing‚ EMNLP 2024‚ Miami‚ Florida‚ November 12−16‚ 2024. November, 2024.
Details about Fool Me Once? Contrasting Vision− and Language−based Explanations in a Clinical Decision−Support Setting | BibTeX data for Fool Me Once? Contrasting Vision− and Language−based Explanations in a Clinical Decision−Support Setting
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[121]
From Classical to Consistent Query Answering under Existential Rules
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Andreas Pieris and Gerardo I. Simari
In Andrea Calì and Maria−Esther Vidal, editors, Proceedings of the 9th Alberto Mendelzon International Workshop on Foundations of Data Management‚ AMW 2015‚ Lima‚ Peru‚ May 6−8‚ 2015.. Vol. 1378 of CEUR Workshop Proceedings. Pages 40−45. CEUR−WS.org. 2015.
Details about From Classical to Consistent Query Answering under Existential Rules | BibTeX data for From Classical to Consistent Query Answering under Existential Rules | Link to From Classical to Consistent Query Answering under Existential Rules
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[122]
From Classical to Consistent Query Answering under Existential Rules
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Andreas Pieris and Gerardo I. Simari
In Blai Bonet and Sven Koenig, editors, Proceedings of the 29th National Conference on Artificial Intelligence‚ AAAI 2015‚ Austin‚ Texas‚ USA‚ January 25−29‚ 2015. Pages 1546−1552. AAAI Press. January, 2015.
Details about From Classical to Consistent Query Answering under Existential Rules | BibTeX data for From Classical to Consistent Query Answering under Existential Rules | Link to From Classical to Consistent Query Answering under Existential Rules
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[123]
Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web
Thomas Lukasiewicz
In Thomas Eiter‚ Enrico Franconi‚ Ralph Hodgson and Susie Stephens, editors, Proceedings of the 2nd International Conference on Rules and Rule Markup Languages for the Semantic Web‚ RuleML 2006‚ Athens‚ Georgia‚ USA‚ November 10−11‚ 2006. Pages 89−96. IEEE Computer Society. 2006.
Details about Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web | BibTeX data for Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web | Link to Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web
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[124]
Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web
Thomas Lukasiewicz
In Fundamenta Informaticae. Vol. 82. No. 3. Pages 289–310. May, 2008.
Details about Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web | BibTeX data for Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web | Link to Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web
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[125]
Game−Theoretic Agent Programming in Golog
Alberto Finzi and Thomas Lukasiewicz
In Ramon López de Mántaras and Lorenza Saitta, editors, Proceedings of the 16th Eureopean Conference on Artificial Intelligence‚ ECAI 2004‚ Valencia‚ Spain‚ August 22−27‚ 2004. Pages 23−27. IOS Press. 2004.
Details about Game−Theoretic Agent Programming in Golog | BibTeX data for Game−Theoretic Agent Programming in Golog | Download (pdf) of Game−Theoretic Agent Programming in Golog
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[126]
Game−Theoretic Agent Programming in Golog Under Partial Observability
Alberto Finzi and Thomas Lukasiewicz
In Christian Freksa‚ Michael Kohlhase and Kerstin Schill, editors, Proceedings of the 29th German Conference on Artificial Intelligence‚ KI 2006‚ Bremen‚ Germany‚ June 14−17‚ 2006. Vol. 4314 of Lecture Notes in Computer Science. Pages 113−127. Springer. 2007.
Details about Game−Theoretic Agent Programming in Golog Under Partial Observability | BibTeX data for Game−Theoretic Agent Programming in Golog Under Partial Observability | Link to Game−Theoretic Agent Programming in Golog Under Partial Observability
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[127]
Game−Theoretic Agent Programming in Golog under Partial Observability
Alberto Finzi and Thomas Lukasiewicz
In P. Gmytrasiewicz and S. Parsons, editors, Proceedings of the IJCAI−2005 Workshop on Game−Theoretic and Decision−Theoretic Agents‚ GTDT 2005‚ Edinburgh‚ Scotland‚ UK‚ July 2005. 2005.
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[128]
Game−Theoretic Golog under Partial Observability
Alberto Finzi and Thomas Lukasiewicz
In Frank Dignum‚ Virginia Dignum‚ Sven Koenig‚ Sarit Kraus‚ Munindar P. Singh and Michael Wooldridge, editors, Proceedings of the 4th International Joint Conference on Autonomous Agents and Multiagent Systems‚ AAMAS 2005‚ Utrecht‚ The Netherlands‚ July 25−29‚ 2005. Pages 1301−1302. ACM Press. 2005.
Details about Game−Theoretic Golog under Partial Observability | BibTeX data for Game−Theoretic Golog under Partial Observability | Link to Game−Theoretic Golog under Partial Observability
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[129]
Game−Theoretic Reasoning About Actions in Nonmonotonic Causal Theories
Alberto Finzi and Thomas Lukasiewicz
In Chitta Baral‚ Gianluigi Greco‚ Nicola Leone and Giorgio Terracina, editors, Proceedings of the 8th International Conference on Logic Programming and Nonmonotonic Reasoning‚ LPNMR 2005‚ Diamante‚ Italy‚ September 5−8‚ 2005. Vol. 3662 of Lecture Notes in Computer Science. Pages 185−197. Springer. 2005.
Details about Game−Theoretic Reasoning About Actions in Nonmonotonic Causal Theories | BibTeX data for Game−Theoretic Reasoning About Actions in Nonmonotonic Causal Theories | Link to Game−Theoretic Reasoning About Actions in Nonmonotonic Causal Theories
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[130]
Generalized Consistent Query Answering under Existential Rules
Thomas Eiter‚ Thomas Lukasiewicz and Livia Predoiu
In James P. Delgrande and Frank Wolter, editors, Proceedings of the 15th International Conference on the Principles of Knowledge Representation and Reasoning‚ KR 2016‚ Cape Town‚ South Africa‚ April 25−29‚ 2016. Pages 359−368. AAAI Press. April, 2016.
Details about Generalized Consistent Query Answering under Existential Rules | BibTeX data for Generalized Consistent Query Answering under Existential Rules | Link to Generalized Consistent Query Answering under Existential Rules
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[131]
Group Preferences for Query Answering in Datalog+⁄− Ontologies
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Oana Tifrea−Marciuska
In V. S. Subrahmanian W. Liu and J. Wijsen, editors, Proceedings of the 7th International Conference on Scalable Uncertainty Management‚ SUM 2013‚ Washington DC‚ USA‚ September 16−18‚ 2013. Vol. 8078 of Lecture Notes in Computer Science. Pages 360−373. Springer. 2013.
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[132]
Hard Regularization to Prevent Deep Online Clustering Collapse without Data Augmentation
Louis Mahon and Thomas Lukasiewicz
In Proceedings of the 38th AAAI Conference on Artificial Intelligence‚ AAAI 2024‚ Vancouver‚ BC‚ Canada‚ February 22 – 25‚ 2024. AAAI Press. February, 2024.
Details about Hard Regularization to Prevent Deep Online Clustering Collapse without Data Augmentation | BibTeX data for Hard Regularization to Prevent Deep Online Clustering Collapse without Data Augmentation
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[133]
Heuristic Ranking in Tightly Coupled Probabilistic Description Logics
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Giorgio Orsi and Gerardo I. Simari
In Nando de Freitas and Kevin P. Murphy, editors, Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence‚ UAI 2012‚ Catalina Island‚ CA‚ USA‚ August 14−18‚ 2012. Pages 554−563. AUAI Press. 2012.
Details about Heuristic Ranking in Tightly Coupled Probabilistic Description Logics | BibTeX data for Heuristic Ranking in Tightly Coupled Probabilistic Description Logics | Link to Heuristic Ranking in Tightly Coupled Probabilistic Description Logics
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[134]
Hi−BEHRT: Hierarchical Transformer−Based Model for Accurate Prediction of Clinical Events Using Multimodal Longitudinal Electronic Health Records
Yikuan Li‚ Mohammad Mamouei‚ Gholamreza Salimi−Khorshidi‚ Shishir Rao‚ Abdelaali Hassaine‚ Dexter Canoy‚ Thomas Lukasiewicz and Kazem Rahimi
In IEEE Journal of Biomedical and Health Informatics. Vol. 27. No. 2. Pages 1106–1117. November, 2023.
Details about Hi−BEHRT: Hierarchical Transformer−Based Model for Accurate Prediction of Clinical Events Using Multimodal Longitudinal Electronic Health Records | BibTeX data for Hi−BEHRT: Hierarchical Transformer−Based Model for Accurate Prediction of Clinical Events Using Multimodal Longitudinal Electronic Health Records | Link to Hi−BEHRT: Hierarchical Transformer−Based Model for Accurate Prediction of Clinical Events Using Multimodal Longitudinal Electronic Health Records
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[135]
How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
Mihaela Catalina Stoian‚ Salijona Dyrmishi‚ Maxime Cordy‚ Thomas Lukasiewicz and Eleonora Giunchiglia
In Proceedings of the 12th International Conference on Learning Representations‚ ICLR 2024‚ Vienna‚ Austria‚ 7–11 May 2024. May, 2024.
Details about How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data | BibTeX data for How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
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[136]
Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation
Zhenghua Xu‚ Di Yuan‚ Thomas Lukasiewicz‚ Cheng Chen‚ Yishu Miao and Guizhi Xu
In Proceedings of the 2020 IEEE International Conference on Acoustics‚ Speech and Signal Processing‚ ICASSP 2020‚ Barcelona‚ Spain‚ May 4–8‚ 2020. IEEE Computer Society. May, 2020.
Details about Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation | BibTeX data for Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation | Link to Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation
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[137]
Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation
Zhenghua Xu‚ Cheng Chen‚ Thomas Lukasiewicz and Yishu Miao
2017.
Details about Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation | BibTeX data for Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation | Link to Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation
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[138]
Hybrid Reinforced Medical Report Generation with M−Linear Attention and Repetition Penalty
Zhenghua Xu‚ Wenting Xu‚ Ruizhi Wang‚ Junyang Chen‚ Chang Qi and Thomas Lukasiewicz
In IEEE Transactions on Neural Networks and Learning Systems. 2023.
Accepted for publication
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[139]
Image−to−Image Translation with Text Guidance
Bowen Li‚ Philip Torr and Thomas Lukasiewicz
In Proceedings of the 33rd British Machine Vision Conference 2022‚ BMVC 2022‚ London‚ UK‚ November 21−24‚ 2022. Pages 581. November, 2022.
Details about Image−to−Image Translation with Text Guidance | BibTeX data for Image−to−Image Translation with Text Guidance | Link to Image−to−Image Translation with Text Guidance
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[140]
Improving Language Models’ Meaning Understanding and Consistency by Learning Conceptual Roles from Dictionary
Myeongjun Erik Jang and Thomas Lukasiewicz
In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing‚ EMNLP 2023‚ Singapore‚ December 6−10‚ 2023. Association for Computational Linguistics. December, 2023.
Details about Improving Language Models’ Meaning Understanding and Consistency by Learning Conceptual Roles from Dictionary | BibTeX data for Improving Language Models’ Meaning Understanding and Consistency by Learning Conceptual Roles from Dictionary
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[141]
Improving Personalized Search on the Social Web Based on Similarities Between Users
Zhenghua Xu‚ Thomas Lukasiewicz and Oana Tifrea−Marciuska
In Umberto Straccia and Andrea Calì, editors, Proceedings of the 8th International Conference on Scalable Uncertainty Management‚ SUM 2014‚ Oxford‚ UK‚ September 15−17‚ 2014. Vol. 8720 of Lecture Notes in Computer Science. Pages 306−319. Springer. 2014.
Details about Improving Personalized Search on the Social Web Based on Similarities Between Users | BibTeX data for Improving Personalized Search on the Social Web Based on Similarities Between Users | Link to Improving Personalized Search on the Social Web Based on Similarities Between Users
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[142]
Inconsistency Handling in Datalog+⁄− Ontologies
Thomas Lukasiewicz‚ Maria Vanina Martinez and Gerardo I. Simari
In Luc De Raedt‚ Christian Bessière‚ Didier Dubois‚ Patrick Doherty‚ Paolo Frasconi‚ Fredrik Heintz and Peter J. F. Lucas, editors, Proceedings of the 20th European Conference on Artificial Intelligence‚ ECAI 2012‚ Montpellier‚ France‚ August 27−31‚ 2012. Vol. 242 of Frontiers in Artificial Intelligence and Applications. Pages 558−563. IOS Press. 2012.
Details about Inconsistency Handling in Datalog+⁄− Ontologies | BibTeX data for Inconsistency Handling in Datalog+⁄− Ontologies | Link to Inconsistency Handling in Datalog+⁄− Ontologies
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[143]
Inconsistency−Tolerant Query Answering for Existential Rules
Thomas Lukasiewicz‚ Enrico Malizia‚ Maria Vanina Martinez‚ Cristian Molinaro‚ Andreas Pieris and Gerardo I. Simari
In Artificial Intelligence. Vol. 307. Pages 103685. June, 2022.
Details about Inconsistency−Tolerant Query Answering for Existential Rules | BibTeX data for Inconsistency−Tolerant Query Answering for Existential Rules | Link to Inconsistency−Tolerant Query Answering for Existential Rules
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[144]
Inconsistency−Tolerant Query Rewriting for Linear Datalog+⁄−
Thomas Lukasiewicz‚ Maria Vanina Martinez and Gerardo I. Simari
In Pablo Barceló and Reinhard Pichler, editors, Proceedings of the 2nd International Workshop on Datalog in Academia and Industry‚ Datalog 2.0‚ Vienna‚ Austria‚ September 11−13‚ 2012. Vol. 7494 of Lecture Notes in Computer Science. Pages 123−134. Springer. 2012.
Details about Inconsistency−Tolerant Query Rewriting for Linear Datalog+⁄− | BibTeX data for Inconsistency−Tolerant Query Rewriting for Linear Datalog+⁄− | Link to Inconsistency−Tolerant Query Rewriting for Linear Datalog+⁄−
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[145]
Inductive Query Answering and Concept Retrieval Exploiting Local Models
Claudia d'Amato‚ Nicola Fanizzi‚ Floriana Esposito and Thomas Lukasiewicz
In Proceedings of the 9th International Conference on Intelligent Systems Design and Applications‚ ISDA 2009‚ Pisa‚ Italy‚ November 30−December 2‚ 2009. Pages 1209−1214. IEEE Computer Society. 2009.
Details about Inductive Query Answering and Concept Retrieval Exploiting Local Models | BibTeX data for Inductive Query Answering and Concept Retrieval Exploiting Local Models | Link to Inductive Query Answering and Concept Retrieval Exploiting Local Models
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[146]
Inductive Reasoning and Semantic Web Search
Claudia d'Amato‚ Floriana Esposito‚ Nicola Fanizzi‚ Bettina Fazzinga‚ Georg Gottlob and Thomas Lukasiewicz
In Sung Y. Shin‚ Sascha Ossowski‚ Michael Schumacher‚ Mathew J. Palakal and Chih−Cheng Hung, editors, Proceedings of the 25th ACM Symposium on Applied Computing‚ SAC 2010‚ Sierre‚ Switzerland‚ March 22−26‚ 2010. Pages 1446−1447. ACM Press. 2010.
Details about Inductive Reasoning and Semantic Web Search | BibTeX data for Inductive Reasoning and Semantic Web Search | Link to Inductive Reasoning and Semantic Web Search
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[147]
Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation
Yuhang Song‚ Beren Millidge‚ Tommaso Salvatori‚ Thomas Lukasiewicz‚ Zhenghua Xu and Rafal Bogacz
In Nature Neuroscience. 2024.
Details about Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation | BibTeX data for Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation | Link to Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation
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[148]
Information Integration with Provenance on the Semantic Web via Probabilistic Datalog+/
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Livia Predoiu and Gerardo I. Simari
No. RR−15−01. DCS. 2015.
Details about Information Integration with Provenance on the Semantic Web via Probabilistic Datalog+/ | BibTeX data for Information Integration with Provenance on the Semantic Web via Probabilistic Datalog+/ | Download (pdf) of Information Integration with Provenance on the Semantic Web via Probabilistic Datalog+/
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[149]
Information Integration with Provenance on the Semantic Web via Probabilistic Datalog+⁄−
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Livia Predoiu and Gerardo Simari
In Fernando Bobillo‚ Rommel Carvalho‚ Paulo C. G. Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Matthias Nickles and Michael Pool, editors, Uncertainty Reasoning for the Semantic Web III‚ International Workshops URSW 2011−2013‚ Held at ISWC‚ Revised Selected Papers. Vol. 8816 of Lecture Notes in Computer Science. Pages 41−62. Springer. 2014.
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[150]
Information Integration with Provenance on the Semantic Web via Probabilistic Datalog+⁄−
Thomas Lukasiewicz and Livia Predoiu
In Fernando Bobillo‚ Rommel N. Carvalho‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Trevor Martin‚ Matthias Nickles and Michael Pool, editors, Proceedings of the 9th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2013‚ Sydney‚ Australia‚ October 21‚ 2013. Vol. 1073 of CEUR Workshop Proceedings. Pages 3−14. CEUR−WS.org. 2013.
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[151]
Introducing Ontological CP−Nets
Tommaso Di Noia and Thomas Lukasiewicz
In Fernando Bobillo‚ Rommel N. Carvalho‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Trevor Martin‚ Matthias Nickles and Michael Pool, editors, Proceedings of the 8th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2012‚ Boston‚ USA‚ November 11‚ 2012. Vol. 900 of CEUR Workshop Proceedings. Pages 90−93. CEUR−WS.org. 2012.
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[152]
Issues in Uncertainty in AI
Gabriele Kern−Isberner‚ Thomas Lukasiewicz and Emil Weydert
In International Journal of Uncertainty‚ Fuzziness and Knowledge−Based Systems. Vol. 11. No. supp02. Pages v−vi. November, 2003.
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[153]
KNOW How to Make Up Your Mind! Adversarially Detecting and Remedying Inconsistencies in Natural Language Explanations
Myeongjun Jang‚ Bodhisattwa Prasad Majumder‚ Julian McAuley‚ Thomas Lukasiewicz and Oana−Maria Camburu
In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics‚ ACL 2023‚ Toronto‚ Canada‚ July 9–14‚ 2023. Association for Computational Linguistics. July, 2023.
Details about KNOW How to Make Up Your Mind! Adversarially Detecting and Remedying Inconsistencies in Natural Language Explanations | BibTeX data for KNOW How to Make Up Your Mind! Adversarially Detecting and Remedying Inconsistencies in Natural Language Explanations
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[154]
Knowledge Base Completion Meets Transfer Learning
Vid Kocijan and Thomas Lukasiewicz
In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing‚ EMNLP 2021‚ Online and in the Barceló Bávaro Convention Centre‚ Punta Cana‚ Dominican Republic‚ November 7–11‚ 2021. November, 2021.
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[155]
Knowledge Graph Extraction from Videos
Louis Mahon‚ Eleonora Giunchiglia‚ Bowen Li and Thomas Lukasiewicz
In Proceedings of the IEEE 2020 International Conference on Machine Learning and Applications‚ ICMLA 2020‚ Miami‚ Florida‚ December 14−17‚ 2020. Pages 25–32. IEEE. December, 2020.
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[156]
Knowledge−Grounded Self−Rationalization via Extractive and Natural Language Explanations
Bodhisattwa Prasad Majumder‚ Oana−Maria Camburu‚ Thomas Lukasiewicz and Julian McAuley
In Kamalika Chaudhuri‚ Stefanie Jegelka‚ Le Song‚ Csaba Szepesvari‚ Gang Niu and Sivan Sabato, editors, Proceedings of the 39th International Conference on Machine Learning‚ ICML 2022‚ Baltimore‚ Maryland‚ USA‚ 17−23 July 2022. Vol. 162 of Proceedings of Machine Learning Research. Pages 14786–14801. PMLR. July, 2022.
Details about Knowledge−Grounded Self−Rationalization via Extractive and Natural Language Explanations | BibTeX data for Knowledge−Grounded Self−Rationalization via Extractive and Natural Language Explanations | Link to Knowledge−Grounded Self−Rationalization via Extractive and Natural Language Explanations
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[157]
Large Language Models for Mathematicians
Simon Frieder‚ Julius Berner‚ Philipp Petersen and Thomas Lukasiewicz
In International Mathematical News. Vol. 254. Pages 1–20. December, 2023.
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[158]
Learning Structured Video Descriptions: Automated Video Knowledge Extraction for Video Understanding Tasks
Daniel Vasile and Thomas Lukasiewicz
In Hervé Panetto‚ Christophe Debruyne‚ Henderik A. Proper‚ Claudio Agostino Ardagna‚ Dumitru Roman and Robert Meersman, editors, On the Move to Meaningful Internet Systems. OTM 2018 Conferences: Confederated International Conferences: CoopIS‚ C&TC‚ and ODBASE 2018‚ Valletta‚ Malta‚ October 23−24‚ 2018. Vol. 11230 of Lecture Notes in Computer Science. Pages 315−332. Springer. October, 2018.
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[159]
Learning from the Best: Rationalizing Predictions by Adversarial Information Calibration
Lei Sha‚ Oana−Maria Camburu and Thomas Lukasiewicz
In Kevin Leyton−Brown and Mausam, editors, Proceedings of the 35th AAAI Conference on Artificial Intelligence‚ AAAI 2021‚ Virtual Conference‚ February 2–9‚ 2021. AAAI Press. 2021.
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[160]
Learning on Arbitrary Graph Topologies via Predictive Coding
Tommaso Salvatori‚ Luca Pinchetti‚ Beren Millidge‚ Yuhang Song‚ Tianyi Bao‚ Rafal Bogacz and Thomas Lukasiewicz
In Proceedings of the 36th Annual Conference on Neural Information Processing Systems‚ NeurIPS 2022‚ New Orleans‚ Louisiana‚ USA. Pages 38232–38244. November, 2022.
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[161]
Learning to Model Multimodal Semantic Alignment for Story Visualization
Bowen Li and Thomas Lukasiewicz
In Findings of EMNLP 2022. Pages 4712–4718. Association for Computational Linguistics. December, 2022.
Details about Learning to Model Multimodal Semantic Alignment for Story Visualization | BibTeX data for Learning to Model Multimodal Semantic Alignment for Story Visualization | Link to Learning to Model Multimodal Semantic Alignment for Story Visualization
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[162]
Learning to Reason: Leveraging Neural Networks for Approximate DNF Counting
Ralph Abboud‚ İsmail İlkan Ceylan and Thomas Lukasiewicz
In Vincent Conitzer and Fei Sha, editors, Proceedings of the 34th AAAI Conference on Artificial Intelligence‚ AAAI 2020‚ New York‚ New York‚ USA‚ February 7–12‚ 2020. AAAI Press. February, 2020.
Details about Learning to Reason: Leveraging Neural Networks for Approximate DNF Counting | BibTeX data for Learning to Reason: Leveraging Neural Networks for Approximate DNF Counting | Link to Learning to Reason: Leveraging Neural Networks for Approximate DNF Counting
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[163]
Lightweight Generative Adversarial Networks for Text−Guided Image Manipulation
Bowen Li‚ Xiaojuan Qi‚ Philip H. S. Torr and Thomas Lukasiewicz
In Proceedings of the 34th Annual Conference on Neural Information Processing Systems‚ NeurIPS 2020‚ December 6–12‚ 2020. December, 2020.
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[164]
Lightweight Tag−Aware Personalized Recommendation on the Social Web Using Ontological Similarity
Zhenghua Xu‚ Oana Tifrea−Marciuska‚ Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Cheng Chen
In IEEE Access. Vol. 6. No. 1. Pages 35590−35610. July, 2018.
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[165]
Lightweight Visual Question Answering using Scene Graphs
Vidyaranya Sai Nuthalapati‚ Ramraj Chandradevan‚ Eleonora Giunchiglia‚ Bowen Li‚ Maxime Kayser‚ Thomas Lukasiewicz and Carl Yang
In Proceedings of the 30th International Conference on Information and Knowledge Management‚ CIKM 2021‚ Gold Coast‚ Queensland‚ Australia‚ November 1–5‚ 2021. ACM Press. November, 2021.
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[166]
Local Probabilistic Deduction from Taxonomic and Probabilistic Knowledge−Bases over Conjunctive Events
Thomas Lukasiewicz
In International Journal of Approximate Reasoning. Vol. 21. No. 1. Pages 23–61. May, 1999.
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[167]
Location−Aware News Recommendation Using Deep Localized Semantic Analysis
Cheng Chen‚ Thomas Lukasiewicz‚ Xiangwu Meng and Zhenghua Xu
In Selçuk Candan‚ Lei Chen and Torben Bach Pedersen, editors, Proceedings of the 22nd International Conference on Database Systems for Advanced Applications‚ DASFAA 2017‚ Suzhou‚ China‚ March 27−30‚ 2017. Vol. 10177 of Lecture Notes in Computer Science. Pages 507–524. Springer. 2017.
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[168]
Location−Aware Personalized News Recommendation with Deep Semantic Analysis
Cheng Chen‚ Xiangwu Meng‚ Zhenghua Xu and Thomas Lukasiewicz.
In IEEE Access. Vol. 5. Pages 1624–1638. January, 2017.
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[169]
Logical Approaches to Imprecise Probabilities
Thomas Lukasiewicz
In International Journal of Approximate Reasoning. Vol. 49. No. 1. Pages 1–2. September, 2008.
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[170]
Long Text Analysis Using Sliced Recurrent Neural Networks with Breaking Point Information Enrichment
Bo Li‚ Zehua Cheng‚ Zhenghua Xu‚ Wei Ye‚ Thomas Lukasiewicz and Shikun Zhang
In Proceedings of the 2019 IEEE International Conference on Acoustics‚ Speech and Signal Processing‚ ICASSP 2019‚ Brighton‚ UK‚ May 12−17‚ 2019. IEEE Computer Society. May, 2019.
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[171]
MPS−AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self−Supervised Medical Image Segmentation
Xiangtao Wang‚ Ruizhi Wang‚ Tian Biao‚ Jiaojiao Zhang‚ Shuo Zhang‚ Junyang Chen‚ Thomas Lukasiewicz and Zhenghua Xu
In Proceedings of the IEEE International Conference on Acoustics‚ Speech and Signal Processing‚ ICASSP 2023‚ Rhodes Island‚ Greece‚ 4−10 June 2023. IEEE. 2023.
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[172]
Machine Learning with Requirements: A Manifesto
Eleonora Giunchiglia‚ Fergus Imrie‚ Mihaela van der Schaar and Thomas Lukasiewicz
In Neurosymbolic Artificial Intelligence. 2024.
In press.
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[173]
Magic Inference Rules for Probabilistic Deduction under Taxonomic Knowledge
Thomas Lukasiewicz
In Gregory F. Cooper and Serafín Moral, editors, Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence‚ UAI 1998‚ Madison‚ Wisconsin‚ USA‚ July 24−26‚ 1998. Pages 354−361. Morgan Kaufmann. 1998.
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[174]
Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations
Oana−Maria Camburu‚ Brendan Shillingford‚ Pasquale Minervini‚ Thomas Lukasiewicz and Phil Blunsom
In Joyce Chai‚ Natalie Schluter and Joel Tetreault, editors, Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics‚ ACL 2020‚ Seattle‚ Washington‚ USA‚ July 5 − 10‚ 2020. Association for Computational Linguistics. July, 2020.
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[175]
Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations
Oana−Maria Camburu‚ Brendan Shillingford‚ Pasquale Minervini‚ Thomas Lukasiewicz and Phil Blunsom
2019.
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[176]
Managing Uncertainty and Vagueness in Description Logics for the Semantic Web
Thomas Lukasiewicz and Umberto Straccia
In Journal of Web Semantics. Vol. 6. No. 4. Pages 291−308. November, 2008.
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[177]
ManiGAN: Text−Guided Image Manipulation
Bowen Li‚ Xiaojuan Qi‚ Thomas Lukasiewicz and Philip H. S. Torr
In Ce Liu‚ Greg Mori‚ Kate Saenko and Silvio Savarese, editors, Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition‚ CVPR 2020‚ Seattle‚ Washington‚ USA‚ June 14−19‚ 2020. Pages 7880–7889. CVF/IEEE. June, 2020.
Details about ManiGAN: Text−Guided Image Manipulation | BibTeX data for ManiGAN: Text−Guided Image Manipulation | DOI (https://doi.org/10.1109/CVPR42600.2020.00790) | Link to ManiGAN: Text−Guided Image Manipulation
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[178]
Many Facets of Reasoning Under Uncertainty‚ Inconsistency‚ Vagueness‚ and Preferences: A Brief Survey
Gabriele Kern−Isberner and Thomas Lukasiewicz
In Künstliche Intelligenz. Vol. 31. No. 1. Pages 9–13. March, 2017.
Details about Many Facets of Reasoning Under Uncertainty‚ Inconsistency‚ Vagueness‚ and Preferences: A Brief Survey | BibTeX data for Many Facets of Reasoning Under Uncertainty‚ Inconsistency‚ Vagueness‚ and Preferences: A Brief Survey | Link to Many Facets of Reasoning Under Uncertainty‚ Inconsistency‚ Vagueness‚ and Preferences: A Brief Survey
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[179]
Many−Valued Disjunctive Logic Programs with Probabilistic Semantics
Thomas Lukasiewicz
In Michael Gelfond‚ Nicola Leone and Gerald Pfeifer, editors, Proceedings of the 5th International Conference on Logic Programming and Nonmonotonic Reasoning‚ LPNMR 1999‚ El Paso‚ Texas‚ USA‚ December 2−4‚ 1999. Vol. 1730 of Lecture Notes in Computer Science. Pages 277−289. Springer. 1999.
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[180]
Many−Valued First−Order Logics with Probabilistic Semantics
Thomas Lukasiewicz
In Georg Gottlob‚ Etienne Grandjean and Katrin Seyr, editors, Proceedings of the 12th International Workshop on Computer Science Logic‚ CSL 1998‚ Annual Conference of the EACSL‚ Brno‚ Czech Republic‚ August 24−28‚ 1998. Vol. 1584 of Lecture Notes in Computer Science. Pages 415−429. Springer. 1999.
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[181]
Mathematical Capabilities of ChatGPT
Simon Frieder‚ Luca Pinchetti‚ Alexis Chevalier‚ Ryan−Rhys Griffiths‚ Tommaso Salvatori‚ Thomas Lukasiewicz‚ Philipp Christian Petersen and Julius Berner
In Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 3‚ NeurIPS Datasets and Benchmarks 2023‚ December 2023. December, 2023.
Details about Mathematical Capabilities of ChatGPT | BibTeX data for Mathematical Capabilities of ChatGPT
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[182]
Mega−Reward: Achieving Human−Level Play without Extrinsic Rewards
Yuhang Song‚ Jianyi Wang‚ Thomas Lukasiewicz‚ Zhenghua Xu‚ Shangtong Zhang‚ Andrzej Wojcicki and Mai Xu
In Vincent Conitzer and Fei Sha, editors, Proceedings of the 34th National Conference on Artificial Intelligence‚ AAAI 2020‚ New York‚ New York‚ USA‚ February 7–12‚ 2020. AAAI Press. February, 2020.
Details about Mega−Reward: Achieving Human−Level Play without Extrinsic Rewards | BibTeX data for Mega−Reward: Achieving Human−Level Play without Extrinsic Rewards | Link to Mega−Reward: Achieving Human−Level Play without Extrinsic Rewards
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[183]
Memory−Driven Text−to−Image Generation
Bowen Li‚ Philip Torr and Thomas Lukasiewicz
In Proceedings of the 33rd British Machine Vision Conference 2022‚ BMVC 2022‚ London‚ UK‚ November 21−24‚ 2022. Pages 726. November, 2022.
Details about Memory−Driven Text−to−Image Generation | BibTeX data for Memory−Driven Text−to−Image Generation | Link to Memory−Driven Text−to−Image Generation
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[184]
Minimum Description Length Clustering to Measure Meaningful Image Complexity
Louis Mahon and Thomas Lukasiewicz
In Pattern Recognition. Vol. 145. No. 109889. January, 2024.
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[185]
Most Probable Explanations for Probabilistic Database Queries
İsmail İlkan Ceylan‚ Stefan Borgwardt and Thomas Lukasiewicz
In Carles Sierra, editor, Proceedings of the 26th International Joint Conference on Artificial Intelligence‚ IJCAI 2017‚ Melbourne‚ Australia‚ August 19−25‚ 2017. Pages 950–956. IJCAI/AAAI Press. August, 2017.
Details about Most Probable Explanations for Probabilistic Database Queries | BibTeX data for Most Probable Explanations for Probabilistic Database Queries | Download (pdf) of Most Probable Explanations for Probabilistic Database Queries
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[186]
Multi−ConDoS: Multimodal Contrastive Domain Sharing Generative Adversarial Networks for Self−Supervised Medical Image Segmentation
Jiaojiao Zhang‚ Shuo Zhang‚ Xiaoqian Shen‚ Thomas Lukasiewicz and Zhenghua Xu
In IEEE Transactions on Medical Imaging. 2023.
Details about Multi−ConDoS: Multimodal Contrastive Domain Sharing Generative Adversarial Networks for Self−Supervised Medical Image Segmentation | BibTeX data for Multi−ConDoS: Multimodal Contrastive Domain Sharing Generative Adversarial Networks for Self−Supervised Medical Image Segmentation
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[187]
Multi−Head Feature Pyramid Networks for Breast Mass Detection
Hexiang Zhang‚ Zhenghua Xu‚ Dan Yao‚ Shuo Zhang‚ Junyang Chen and Thomas Lukasiewicz
In Proceedings of the IEEE International Conference on Acoustics‚ Speech and Signal Processing‚ ICASSP 2023‚ Rhodes Island‚ Greece‚ 4−10 June 2023. IEEE. 2023.
Details about Multi−Head Feature Pyramid Networks for Breast Mass Detection | BibTeX data for Multi−Head Feature Pyramid Networks for Breast Mass Detection
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[188]
Multi−Label Classification Neural Networks with Hard Logical Constraints
Eleonora Giunchiglia and Thomas Lukasiewicz
In Journal of Artificial Intelligence Research. Vol. 72. Pages 759–818. November, 2021.
Details about Multi−Label Classification Neural Networks with Hard Logical Constraints | BibTeX data for Multi−Label Classification Neural Networks with Hard Logical Constraints | Link to Multi−Label Classification Neural Networks with Hard Logical Constraints
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[189]
Multi−Modal Contrastive Mutual Learning and Pseudo−Label Re−Learning for Semi−Supervised Medical Image Segmentation
Shuo Zhang‚ Jiaojiao Zhang‚ Biao Tian‚ Thomas Lukasiewicz and Zhenghua Xu
In Medical Image Analysis. Vol. 83. Pages 102656. January, 2023.
Details about Multi−Modal Contrastive Mutual Learning and Pseudo−Label Re−Learning for Semi−Supervised Medical Image Segmentation | BibTeX data for Multi−Modal Contrastive Mutual Learning and Pseudo−Label Re−Learning for Semi−Supervised Medical Image Segmentation | Link to Multi−Modal Contrastive Mutual Learning and Pseudo−Label Re−Learning for Semi−Supervised Medical Image Segmentation
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[190]
Multi−Type Disentanglement without Adversarial Training
Lei Sha and Thomas Lukasiewicz
In Kevin Leyton−Brown and Mausam, editors, Proceedings of the 35th AAAI Conference on Artificial Intelligence‚ AAAI 2021‚ Virtual Conference‚ February 2–9‚ 2021. AAAI Press. 2021.
Details about Multi−Type Disentanglement without Adversarial Training | BibTeX data for Multi−Type Disentanglement without Adversarial Training | Link to Multi−Type Disentanglement without Adversarial Training
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[191]
MvCo−DoT: Multi−View Contrastive Domain Transfer Network for Medical Report Generation
Ruizhi Wang‚ Xiangtao Wang‚ Zhenghua Xu‚ Wenting Xu‚ Junyang Chen and Thomas Lukasiewicz
In Proceedings of the IEEE International Conference on Acoustics‚ Speech and Signal Processing‚ ICASSP 2023‚ Rhodes Island‚ Greece‚ 4−10 June 2023. IEEE. 2023.
Details about MvCo−DoT: Multi−View Contrastive Domain Transfer Network for Medical Report Generation | BibTeX data for MvCo−DoT: Multi−View Contrastive Domain Transfer Network for Medical Report Generation
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[192]
NP−Match: When Neural Processes meet Semi−Supervised Learning
Jianfeng Wang‚ Thomas Lukasiewicz‚ Daniela Massiceti‚ Xiaolin Hu‚ Vladimir Pavlovic and Alexandros Neophytou
In Kamalika Chaudhuri‚ Stefanie Jegelka‚ Le Song‚ Csaba Szepesvari‚ Gang Niu and Sivan Sabato, editors, Proceedings of the 39th International Conference on Machine Learning‚ ICML 2022‚ Baltimore‚ Maryland‚ USA‚ 17−23 July 2022. Vol. 162 of Proceedings of Machine Learning Research. PMLR. July, 2022.
Details about NP−Match: When Neural Processes meet Semi−Supervised Learning | BibTeX data for NP−Match: When Neural Processes meet Semi−Supervised Learning | Link to NP−Match: When Neural Processes meet Semi−Supervised Learning
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[193]
NP−SemiSeg: When Neural Processes meet Semi−Supervised Semantic Segmentation
Jianfeng Wang‚ Daniela Massiceti‚ Xiaolin Hu‚ Vladimir Pavlovic and Thomas Lukasiewicz
In Proceedings of the 40th International Conference on Machine Learning‚ ICML 2023‚ Hawaii‚ USA‚ 23−29 July 2023. July, 2023.
Details about NP−SemiSeg: When Neural Processes meet Semi−Supervised Semantic Segmentation | BibTeX data for NP−SemiSeg: When Neural Processes meet Semi−Supervised Semantic Segmentation
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[194]
Neural Networks for Approximate DNF Counting: An Abridged Report
Ralph Abboud‚ İsmail İlkan Ceylan and Thomas Lukasiewicz
In Lingfei Wu‚ Jian Tang‚ Yinglong Xia and Charu Aggarwal, editors, Proceedings of the 1st International Workshop on Deep Learning on Graphs: Methodologies and Applications‚ DLGMA 2020‚ New York‚ New York‚ USA‚ February 8‚ 2020. February, 2020.
Details about Neural Networks for Approximate DNF Counting: An Abridged Report | BibTeX data for Neural Networks for Approximate DNF Counting: An Abridged Report | Download (pdf) of Neural Networks for Approximate DNF Counting: An Abridged Report
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[195]
New Tractable Cases in Default Reasoning from Conditional Knowledge Bases
Thomas Eiter and Thomas Lukasiewicz
In Manuel Ojeda−Aciego‚ Inman P. de Guzmán‚ Gerhard Brewka and Luís Moniz Pereira, editors, Proceedings of the 7th European Workshop on Logics in Artificial Intelligence‚ JELIA 2000‚ Malaga‚ Spain‚ September 29 − October 2‚ 2000. Vol. 1919 of Lecture Notes in Computer Science. Pages 313−328. Springer. 2000.
Details about New Tractable Cases in Default Reasoning from Conditional Knowledge Bases | BibTeX data for New Tractable Cases in Default Reasoning from Conditional Knowledge Bases | Link to New Tractable Cases in Default Reasoning from Conditional Knowledge Bases
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[196]
NoiER: An Approach for Training more Reliable Fine−Tuned Downstream Task Models
Myeongjun Jang and Thomas Lukasiewicz
In IEEE Transactions on Audio‚ Speech and Language Processing. Vol. 30. Pages 2514–2525. July, 2022.
Details about NoiER: An Approach for Training more Reliable Fine−Tuned Downstream Task Models | BibTeX data for NoiER: An Approach for Training more Reliable Fine−Tuned Downstream Task Models | Link to NoiER: An Approach for Training more Reliable Fine−Tuned Downstream Task Models
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[197]
Nonmonotonic Probabilistic Logics between Model−Theoretic Probabilistic Logic and Probabilistic Logic under Coherence
Thomas Lukasiewicz
In Salem Benferhat and Enrico Giunchiglia, editors, Proceedings of the 9th International Workshop on Non−Monotonic Reasoning‚ NMR 2002‚ Toulouse‚ France‚ April 19−21‚ 2002. Pages 265−274. 2002.
Details about Nonmonotonic Probabilistic Logics between Model−Theoretic Probabilistic Logic and Probabilistic Logic under Coherence | BibTeX data for Nonmonotonic Probabilistic Logics between Model−Theoretic Probabilistic Logic and Probabilistic Logic under Coherence | Download (pdf) of Nonmonotonic Probabilistic Logics between Model−Theoretic Probabilistic Logic and Probabilistic Logic under Coherence
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[198]
Nonmonotonic Probabilistic Logics under Variable−Strength Inheritance with Overriding: Algorithms and Implementation in NMPROBLOG
Thomas Lukasiewicz
In Fabio Gagliardi Cozman‚ Robert Nau and Teddy Seidenfeld, editors, Proceedings of the 4th International Symposium on Imprecise Probabilities and their Applications‚ ISIPTA 2005‚ Pittsburgh‚ PA‚ USA‚ July 20−23‚ 2005. Pages 230−239. SIPTA. 2005.
Details about Nonmonotonic Probabilistic Logics under Variable−Strength Inheritance with Overriding: Algorithms and Implementation in NMPROBLOG | BibTeX data for Nonmonotonic Probabilistic Logics under Variable−Strength Inheritance with Overriding: Algorithms and Implementation in NMPROBLOG | Download (pdf) of Nonmonotonic Probabilistic Logics under Variable−Strength Inheritance with Overriding: Algorithms and Implementation in NMPROBLOG
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[199]
Nonmonotonic Probabilistic Logics under Variable−Strength Inheritance with Overriding: Complexity‚ Algorithms‚ and Implementation
Thomas Lukasiewicz
In International Journal of Approximate Reasoning. Vol. 44. No. 3. Pages 301–321. March, 2007.
Details about Nonmonotonic Probabilistic Logics under Variable−Strength Inheritance with Overriding: Complexity‚ Algorithms‚ and Implementation | BibTeX data for Nonmonotonic Probabilistic Logics under Variable−Strength Inheritance with Overriding: Complexity‚ Algorithms‚ and Implementation | Link to Nonmonotonic Probabilistic Logics under Variable−Strength Inheritance with Overriding: Complexity‚ Algorithms‚ and Implementation
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[200]
Nonmonotonic Probabilistic Reasoning under Variable−Strength Inheritance with Overriding
Thomas Lukasiewicz
In Synthese. Vol. 146. No. 1/2. Pages 153–169. 2005.
Details about Nonmonotonic Probabilistic Reasoning under Variable−Strength Inheritance with Overriding | BibTeX data for Nonmonotonic Probabilistic Reasoning under Variable−Strength Inheritance with Overriding | Link to Nonmonotonic Probabilistic Reasoning under Variable−Strength Inheritance with Overriding
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[201]
On Ontologies and CP−Nets
Tommaso Di Noia and Thomas Lukasiewicz
In Proceedings of the 21st Italian Symposium on Advanced Database Systems‚ SEBD 2013‚ Roccella Jonica‚ Italy‚ June 30 − July 3‚ 2013. 2013.
Details about On Ontologies and CP−Nets | BibTeX data for On Ontologies and CP−Nets
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[202]
On the Complexity of mCP−Nets
Thomas Lukasiewicz and Enrico Malizia
In Dale Schuurmans and Michael Wellman, editors, Proceedings of the 30th National Conference on Artificial Intelligence‚ AAAI 2016‚ Phoenix‚ Arizona‚ USA‚ February 12–17‚ 2016. Pages 558−564. AAAI Press. February, 2016.
Details about On the Complexity of mCP−Nets | BibTeX data for On the Complexity of mCP−Nets | Link to On the Complexity of mCP−Nets
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[203]
Ontological CP−Nets
Tommaso Di Noia‚ Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Oana Tifrea−Marciuska
In Fernando Bobillo‚ Rommel Carvalho‚ Paulo C. G. Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Matthias Nickles and Michael Pool, editors, Uncertainty Reasoning for the Semantic Web III‚ International Workshops URSW 2011−2013‚ Held at ISWC‚ Revised Selected Papers. Vol. 8816 of Lecture Notes in Computer Science. Pages 289−308. Springer. 2014.
Details about Ontological CP−Nets | BibTeX data for Ontological CP−Nets | Link to Ontological CP−Nets
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[204]
Ontological Query Answering under Many−Valued Group Preferences in Datalog+⁄−
Bettina Fazzinga‚ Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Oana Tifrea−Marciuska
In International Journal of Approximate Reasoning. Vol. 93. Pages 354–371. February, 2018.
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[205]
Ontological Reasoning with F−Logic Lite and its Extensions
Andrea Calì‚ Georg Gottlob‚ Michael Kifer‚ Thomas Lukasiewicz and Andreas Pieris
In Maria Fox and David Poole, editors, Proceedings of the 24th AAAI Conference on Artificial Intelligence‚ AAAI 2010‚ Atlanta‚ Georgia‚ USA‚ July 11−15‚ 2010. AAAI Press. 2010.
Details about Ontological Reasoning with F−Logic Lite and its Extensions | BibTeX data for Ontological Reasoning with F−Logic Lite and its Extensions | Link to Ontological Reasoning with F−Logic Lite and its Extensions
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[206]
Ontology Reasoning with Deep Neural Networks
Patrick Hohenecker and Thomas Lukasiewicz
In Journal of Artificial Intelligence Research (JAIR). Vol. 68. Pages 503–540. July, 2020.
Details about Ontology Reasoning with Deep Neural Networks | BibTeX data for Ontology Reasoning with Deep Neural Networks | Link to Ontology Reasoning with Deep Neural Networks
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[207]
Ontology Reasoning with Deep Neural Networks
Patrick Hohenecker and Thomas Lukasiewicz
2018.
Details about Ontology Reasoning with Deep Neural Networks | BibTeX data for Ontology Reasoning with Deep Neural Networks | Link to Ontology Reasoning with Deep Neural Networks
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[208]
Ontology Reasoning with Deep Neural Networks (Extended Abstract)
Patrick Hohenecker and Thomas Lukasiewicz
In Proceedings of the 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence‚ IJCAI−PRICAI 2020‚ Yokohama‚ Japan‚ July 11−17‚ 2020. IJCAI/AAAI Press. July, 2020.
Details about Ontology Reasoning with Deep Neural Networks (Extended Abstract) | BibTeX data for Ontology Reasoning with Deep Neural Networks (Extended Abstract) | Link to Ontology Reasoning with Deep Neural Networks (Extended Abstract)
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[209]
Ontology−Based Query Answering with Group Preferences
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Oana Tifrea−Marciuska
In ACM Transactions on Internet Technology (TOIT). Vol. 14. No. 4. Pages 25:1−25:24. December, 2014.
Details about Ontology−Based Query Answering with Group Preferences | BibTeX data for Ontology−Based Query Answering with Group Preferences | Link to Ontology−Based Query Answering with Group Preferences
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[210]
Ontology−Based Query Answering with Group Preferences
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Oana Tifrea−Marciuska
No. RR−14−02. DCS. May, 2014.
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[211]
Ontology−Based Semantic Search on the Web and its Combination with the Power of Inductive Reasoning
Claudia d'Amato‚ Nicola Fanizzi‚ Bettina Fazzinga‚ Georg Gottlob and Thomas Lukasiewicz
In Annals of Mathematics and Artificial Intelligence. Vol. 65. No. 2/3. Pages 83−121. July, 2012.
Details about Ontology−Based Semantic Search on the Web and its Combination with the Power of Inductive Reasoning | BibTeX data for Ontology−Based Semantic Search on the Web and its Combination with the Power of Inductive Reasoning | Link to Ontology−Based Semantic Search on the Web and its Combination with the Power of Inductive Reasoning
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[212]
Ontology−Mediated Queries for Probabilistic Databases
Stefan Borgwardt‚ İsmail İlkan Ceylan and Thomas Lukasiewicz
In Satinder Singh and Shaul Markovitch, editors, Proceedings of the 31st National Conference on Artificial Intelligence‚ AAAI 2017‚ San Francisco‚ California‚ USA‚ February 4–9‚ 2017. Pages 1063–1069. AAAI Press. 2017.
Details about Ontology−Mediated Queries for Probabilistic Databases | BibTeX data for Ontology−Mediated Queries for Probabilistic Databases | Link to Ontology−Mediated Queries for Probabilistic Databases
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[213]
Ontology−Mediated Query Answering over Log−Linear Probabilistic Data
Stefan Borgwardt‚ İsmail İlkan Ceylan and Thomas Lukasiewicz
In Pascal Van Hentenryck and Zhi−Hua Zhou, editors, Proceedings of the 33rd National Conference on Artificial Intelligence‚ AAAI 2019‚ Honolulu‚ Hawaii‚ USA‚ January 27 − February 1‚ 2019. Pages 2711–2718. AAAI Press. January, 2019.
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[214]
Ontology−Mediated Query Answering over Log−Linear Probabilistic Data (Abstract)
Stefan Borgwardt‚ İsmail İlkan Ceylan and Thomas Lukasiewicz
In Mantas Simkus and Grant E. Weddell, editors, Proceedings of the 32nd International Workshop on Description Logics‚ DL 2019‚ Oslo‚ Norway‚ June 18−21‚ 2019. Vol. 2373 of CEUR Workshop Proceedings. CEUR−WS.org. June, 2019.
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[215]
P−SHOQ(D): A Probabilistic Extension of SHOQ(D) for Probabilistic Ontologies in the Semantic Web
Rosalba Giugno and Thomas Lukasiewicz
In Sergio Flesca‚ Sergio Greco‚ Nicola Leone and Giovambattista Ianni, editors, Proceedings of the 8th European Conference on Logics in Artificial Intelligence‚ JELIA 2002‚ Cosenza‚ Italy‚ September 23−26‚ 2002. Vol. 2424 of Lecture Notes in Computer Science. Pages 86−97. Springer. 2002.
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[216]
PAC−Net: Multi−Pathway FPN with Position Attention Guided Connections and Vertex Distance IoU for 3D Medical Image Detection
Zhenghua Xu‚ Tianrun Li‚ Yunxin Liu‚ Yuefu Zhan‚ Junyang Chen and Thomas Lukasiewicz
In Frontiers in Bioengineering and Biotechnology. Vol. 11. Pages 1049555. February, 2023.
Details about PAC−Net: Multi−Pathway FPN with Position Attention Guided Connections and Vertex Distance IoU for 3D Medical Image Detection | BibTeX data for PAC−Net: Multi−Pathway FPN with Position Attention Guided Connections and Vertex Distance IoU for 3D Medical Image Detection | Link to PAC−Net: Multi−Pathway FPN with Position Attention Guided Connections and Vertex Distance IoU for 3D Medical Image Detection
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[217]
Painless and accurate medical image analysis using deep reinforcement learning with task−oriented homogenized automatic pre−processing
Di Yuan‚ Yunxin Liu‚ Zhenghua Xu‚ Yuefu Zhan‚ Junyang Chen and Thomas Lukasiewicz
In Computers in Biology and Medicine. Vol. 153. Pages 106487. February, 2023.
Details about Painless and accurate medical image analysis using deep reinforcement learning with task−oriented homogenized automatic pre−processing | BibTeX data for Painless and accurate medical image analysis using deep reinforcement learning with task−oriented homogenized automatic pre−processing | Link to Painless and accurate medical image analysis using deep reinforcement learning with task−oriented homogenized automatic pre−processing
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[218]
Partially Observable Game−Theoretic Agent Programming in Golog
Alberto Finzi and Thomas Lukasiewicz
In International Journal of Approximate Reasoning. Vol. 119. Pages 220–241. April, 2020.
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[219]
PhaCIA−TCNs: Short−Term Load Forecasting Using Temporal Convolutional Networks With Parallel Hybrid Activated Convolution and Input Attention
Zhenghua Xu‚ Zhoutao Yu‚ Hexiang Zhang‚ Junyang Chen‚ Junhua Gu‚ Thomas Lukasiewicz and Victor Leung
In IEEE Transactions on Network Science and Engineering. August, 2023.
Details about PhaCIA−TCNs: Short−Term Load Forecasting Using Temporal Convolutional Networks With Parallel Hybrid Activated Convolution and Input Attention | BibTeX data for PhaCIA−TCNs: Short−Term Load Forecasting Using Temporal Convolutional Networks With Parallel Hybrid Activated Convolution and Input Attention | Link to PhaCIA−TCNs: Short−Term Load Forecasting Using Temporal Convolutional Networks With Parallel Hybrid Activated Convolution and Input Attention
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[220]
PiShield: A NeSy Framework for Learning with Requirements
Mihaela Cătălina Stoian‚ Alex Tatomir‚ Eleonora Giunchiglia and Thomas Lukasiewicz
In Proceedings of the 33rd International Joint Conference on Artificial Intelligence‚ IJCAI 2024‚ Demos‚ Jeju Island‚ South Korea‚ August 3–9‚ 2024. ijcai.org. August, 2024.
Details about PiShield: A NeSy Framework for Learning with Requirements | BibTeX data for PiShield: A NeSy Framework for Learning with Requirements
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[221]
Pre−training and Diagnosing Knowledge Base Completion Models
Vid Kocijan‚ Myeongjun Jang and Thomas Lukasiewicz
In Artificial Intelligence. Vol. 329. No. 104081. April, 2024.
Details about Pre−training and Diagnosing Knowledge Base Completion Models | BibTeX data for Pre−training and Diagnosing Knowledge Base Completion Models | Link to Pre−training and Diagnosing Knowledge Base Completion Models
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[222]
Predictive Coding Beyond Gaussian Distributions
Luca Pinchetti‚ Tommaso Salvatori‚ Yordan Yordanov‚ Beren Millidge‚ Yuhang Song and Thomas Lukasiewicz
In Proceedings of the 36th Annual Conference on Neural Information Processing Systems‚ NeurIPS 2022‚ New Orleans‚ Louisiana‚ USA. Pages 1280–1293. November, 2022.
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[223]
Predictive Coding beyond Correlations
Tommaso Salvatori‚ Luca Pinchetti‚ Amine M'Charrak‚ Beren Millidge and Thomas Lukasiewicz
In Proceedings of the 41th International Conference on Machine Learning‚ ICML 2024‚ Vienna‚ Austria‚ 21−27 July 2024. 2024.
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[224]
Predictive Coding: Towards a Future of Deep Learning Beyond Backpropagation?
Beren Millidge‚ Tommaso Salvatori‚ Yuhang Song‚ Rafal Bogacz and Thomas Lukasiewicz
In Luc De Raedt, editor, Proceedings of the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence‚ IJCAI−ECAI 2022‚ Survey Track‚ Vienna‚ Austria‚ July 23−29‚ 2022. Pages 5538–5545. IJCAI/AAAI Press. July, 2022.
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[225]
Preface
Thomas Lukasiewicz and Attila Sali
In Annals of Mathematics and Artificial Intelligence. Vol. 73. No. 1/2. Pages 1−3. January, 2015.
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[226]
Preface
Diego Calvanese and Thomas Lukasiewicz
In Semantic Web. Vol. 4. No. 4. Pages 349. 2013.
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[227]
Preface
Sergio Greco and Thomas Lukasiewicz
In Annals of Mathematics and Artificial Intelligence. Vol. 64. No. 2−3. Pages 109−111. 2012.
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[228]
Preference Queries with Ceteris Paribus Semantics for Linked Data
Jessica Rosati‚ Tommaso Di Noia‚ Thomas Lukasiewicz‚ Renato De Leone and Andrea Maurino
In Christophe Debruyne‚ Hervé Panetto‚ Robert Meersman‚ Tharam S. Dillon‚ Georg Weichhart‚ Yuan An and Claudio Agostino Ardagna, editors, Proceedings of the 14th International Conference on Ontologies‚ Databases‚ and Applications of Semantics‚ ODBASE 2015‚ Rhodes‚ Greece‚ October 26−30‚ 2015. Vol. 9415 of Lecture Notes in Computer Science. Pages 423–442. Springer. 2015.
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[229]
Preference−Based Query Answering in Datalog+⁄− Ontologies
Thomas Lukasiewicz‚ Maria Vanina Martinez and Gerardo I. Simari
In Francesca Rossi, editor, Proceedings of the 23rd International Joint Conference on Artificial Intelligence‚ IJCAI 2013‚ Beijing‚ China‚ August 3−9‚ 2013. Pages 1017−1023. AAAI Press / International Joint Conferences on Artificial Intelligence. 2013.
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[230]
Preference−Based Query Answering in Probabilistic Datalog+⁄− Ontologies
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Oana Tifrea−Marciuska
In Journal on Data Semantics. Vol. 4. No. 2. Pages 81−101. June, 2015.
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[231]
Preference−Based Query Answering in Probabilistic Datalog+⁄− Ontologies
Thomas Lukasiewicz‚ Maria Vanina Martinez and Gerardo I. Simari
In Robert Meersman‚ Hervé Panetto‚ Tharam Dillon‚ Johann Eder‚ Zohra Bellahsene‚ Norbert Ritter‚ Pieter De Leenheer and Deijing Dou, editors, Proceedings of the 12th International Conference on Ontologies‚ Databases‚ and Applications of Semantics‚ ODBASE 2013‚ Graz‚ Austria‚ September 10−11‚ 2013. Vol. 8185 of Lecture Notes in Computer Science. Pages 501−518. Springer. 2013.
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[232]
Preferences‚ Links‚ and Probabilities for Ranking Objects in Ontologies
Thomas Lukasiewicz and Jörg Schellhase
In Paulo Cesar G. da Costa‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Francis Fung and Michael Pool, editors, Proceedings of the 2nd ISWC Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2006‚ Athens‚ Georgia‚ USA‚ November 5‚ 2006. Vol. 218 of CEUR Workshop Proceedings. CEUR−WS.org. 2006.
Details about Preferences‚ Links‚ and Probabilities for Ranking Objects in Ontologies | BibTeX data for Preferences‚ Links‚ and Probabilities for Ranking Objects in Ontologies | Download (pdf) of Preferences‚ Links‚ and Probabilities for Ranking Objects in Ontologies
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[233]
Preference−Based Query Answering in Datalog+⁄− Ontologies
Thomas Lukasiewicz‚ Maria Vanina Martinez and Gerardo I. Simari
In Thomas Eiter‚ Birte Glimm‚ Yevgeny Kazakov and Markus Krötzsch, editors, Proceedings of the 26th International Workshop on Description Logics‚ DL 2013‚ Ulm‚ Germany‚ July 23−26‚ 2013. Vol. 1014 of CEUR Workshop Proceedings. Pages 804−815. CEUR−WS.org. 2013.
Details about Preference−Based Query Answering in Datalog+⁄− Ontologies | BibTeX data for Preference−Based Query Answering in Datalog+⁄− Ontologies | Download (pdf) of Preference−Based Query Answering in Datalog+⁄− Ontologies
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[234]
Preferential Query Answering over the Semantic Web with Possibilistic Networks
Stefan Borgwardt‚ Bettina Fazzinga‚ Thomas Lukasiewicz‚ Akanksha Shrivastava and Oana Tifrea−Marciuska
In Subbarao Kambhampati, editor, Proceedings of the 25th International Joint Conference on Artificial Intelligence‚ IJCAI 2016‚ New York‚ NY‚ USA‚ July 9−15‚ 2016. Pages 994−1000. IJCAI/AAAI Press. July, 2016.
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[235]
Preferred Explanations for Ontology−Mediated Queries under Existential Rules
İsmail İlkan Ceylan‚ Thomas Lukasiewicz‚ Enrico Malizia‚ Cristian Molinaro and Andrius Vaicenavičius
In Kevin Leyton−Brown and Mausam, editors, Proceedings of the 35th AAAI Conference on Artificial Intelligence‚ AAAI 2021‚ Virtual Conference‚ February 2–9‚ 2021. AAAI Press. 2021.
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[236]
Probabilistic Deduction with Conditional Constraints over Basic Events
Thomas Lukasiewicz
In Anthony G. Cohn‚ Lenhart K. Schubert and Stuart C. Shapiro, editors, Proceedings of the 6th International Conference on Principles of Knowledge Representation and Reasoning‚ KR 1998‚ Trento‚ Italy‚ June 2−5‚ 1998. Pages 380−393. Morgan Kaufmann. 1998.
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[237]
Probabilistic Deduction with Conditional Constraints over Basic Events
Thomas Lukasiewicz
In Journal of Artificial Intelligence Research (JAIR). Vol. 10. Pages 199–241. April, 1999.
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[238]
Probabilistic Default Reasoning with Conditional Constraints
Thomas Lukasiewicz
In C. Baral and M. Truszczynski, editors, Proceedings of the 8th International Workshop on Non−Monotonic Reasoning‚ NMR 2000‚ Breckenridge‚ Colorado‚ USA‚ April 2000. Vol. 5. No. 024. 2000.
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[239]
Probabilistic Default Reasoning with Conditional Constraints
Thomas Lukasiewicz
In Annals of Mathematics and Artificial Intelligence. Vol. 34. No. 1–3. Pages 35–88. March, 2002.
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[240]
Probabilistic Description Logic Programs
Thomas Lukasiewicz
In Lluis Godo, editor, Proceedings of the 8th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty‚ ECSQARU 2005‚ Barcelona‚ Spain‚ July 6−8‚ 2005. Vol. 3571 of Lecture Notes in Computer Science. Pages 737−749. Springer. 2005.
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[241]
Probabilistic Description Logic Programs
Thomas Lukasiewicz
In International Journal of Approximate Reasoning. Vol. 45. No. 2. Pages 288–307. July, 2007.
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[242]
Probabilistic Description Logic Programs under Inheritance with Overriding for the Semantic Web
Thomas Lukasiewicz
In International Journal of Approximate Reasoning. Vol. 49. No. 1. Pages 18–34. September, 2008.
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[243]
Probabilistic Lexicographic Entailment under Variable−Strength Inheritance with Overriding
Thomas Lukasiewicz
In Thomas D. Nielsen and Nevin Lianwen Zhang, editors, Proceedings of the 7th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty‚ ECSQARU 2003‚ Aalborg‚ Denmark‚ July 2−5‚ 2003. Vol. 2711 of Lecture Notes in Computer Science. Pages 576−587. Springer. 2003.
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[244]
Probabilistic Logic Programming
Thomas Lukasiewicz
In Proceedings of the 13th European Conference on Artificial Intelligence‚ ECAI 1998‚ Brighton‚ UK‚ August 1998. Pages 388−392. 1998.
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[245]
Probabilistic Logic Programming under Inheritance with Overriding
Thomas Lukasiewicz
In Jack S. Breese and Daphne Koller, editors, Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence‚ UAI 2001‚ Seattle‚ Washington‚ USA‚ August 2−5‚ 2001. Pages 329−336. Morgan Kaufmann. 2001.
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[246]
Probabilistic Logic Programming under Maximum Entropy
Thomas Lukasiewicz and Gabriele Kern−Isberner
In Anthony Hunter and Simon Parsons, editors, Proceedings of the 5th European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty‚ ECSQARU 1999‚ London‚ UK‚ July 5−9‚ 1999. Vol. 1638 of Lecture Notes in Computer Science. Pages 279−292. Springer. 1999.
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[247]
Probabilistic Logic Programming with Conditional Constraints
Thomas Lukasiewicz
In ACM Transactions on Computational Logic (TOCL). Vol. 2. No. 3. Pages 289–339. July, 2001.
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[248]
Probabilistic Logic under Coherence‚ Model−Theoretic Probabilistic Logic‚ and Default Reasoning
Veronica Biazzo‚ Angelo Gilio‚ Thomas Lukasiewicz and Giuseppe Sanfilippo
In Salem Benferhat and Philippe Besnard, editors, Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty‚ ECSQARU 2001‚ Toulouse‚ France‚ September 19−21‚ 2001. Vol. 2143 of Lecture Notes in Computer Science. Pages 290−302. Springer. 2001.
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[249]
Probabilistic Logic under Coherence‚ Model−Theoretic Probabilistic Logic‚ and Default Reasoning in System P
Veronica Biazzo‚ Angelo Gilio‚ Thomas Lukasiewicz and Giuseppe Sanfilippo
In Journal of Applied Non−Classical Logics. Vol. 12. No. 2. Pages 189–213. 2002.
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[250]
Probabilistic Logic under Coherence: Complexity and Algorithms
Veronica Biazzo‚ Angelo Gilio‚ Thomas Lukasiewicz and Giuseppe Sanfilippo
In Gert De Cooman‚ Terrence Fine and Teddy Seidenfeld, editors, Proceedings of the 2nd International Symposium on Imprecise Probabilities and their Applications‚ ISIPTA 2001‚ Ithaca‚ NY‚ USA‚ June 26−29‚ 2001. Pages 51−61. Shaker. 2001.
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[251]
Probabilistic Logic under Coherence: Complexity and Algorithms
Veronica Biazzo‚ Angelo Gilio‚ Thomas Lukasiewicz and Giuseppe Sanfilippo
In Annals of Mathematics and Artificial Intelligence. Vol. 45. No. 1/2. Pages 35–81. October, 2005.
Details about Probabilistic Logic under Coherence: Complexity and Algorithms | BibTeX data for Probabilistic Logic under Coherence: Complexity and Algorithms | Link to Probabilistic Logic under Coherence: Complexity and Algorithms
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[252]
Probabilistic Models over Weighted Orderings: Fixed−Parameter Tractable Variable Elimination
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ David Poole and Gerardo I. Simari
In James P. Delgrande and Frank Wolter, editors, Proceedings of the 15th International Conference on the Principles of Knowledge Representation and Reasoning‚ KR 2016‚ Cape Town‚ South Africa‚ April 25−29‚ 2016. Pages 494−504. AAAI Press. April, 2016.
Details about Probabilistic Models over Weighted Orderings: Fixed−Parameter Tractable Variable Elimination | BibTeX data for Probabilistic Models over Weighted Orderings: Fixed−Parameter Tractable Variable Elimination | Link to Probabilistic Models over Weighted Orderings: Fixed−Parameter Tractable Variable Elimination
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[253]
Probabilistic Object Bases
Thomas Eiter‚ James J. Lu‚ Thomas Lukasiewicz and V. S. Subrahmanian
In ACM Transactions on Database Systems (TODS). Vol. 26. No. 3. Pages 264–312. September, 2001.
Details about Probabilistic Object Bases | BibTeX data for Probabilistic Object Bases | Link to Probabilistic Object Bases
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[254]
Probabilistic Ontological Data Exchange with Bayesian Networks
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Livia Predoiu and Gerardo I. Simari
In Fernando Bobillo‚ Rommel N. Carvalho‚ Davide Ceolin‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Trevor P. Martin‚ Matthias Nickles and Michael Pool, editors, Proceedings of the 11th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2015‚ Bethlehem‚ USA‚ October 12‚ 2015. Vol. 1479 of CEUR Workshop Proceedings. Pages 38−49. CEUR−WS.org. 2015.
Details about Probabilistic Ontological Data Exchange with Bayesian Networks | BibTeX data for Probabilistic Ontological Data Exchange with Bayesian Networks | Download (pdf) of Probabilistic Ontological Data Exchange with Bayesian Networks
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[255]
Probabilistic Preference Logic Networks
Thomas Lukasiewicz‚ Maria Vanina Martinez and Gerardo I. Simari
In Torsten Schaub‚ Gerhard Friedrich and Barry O'Sullivan, editors, Proceedings of the 21st European Conference on Artificial Intelligence‚ ECAI 2014‚ Prague‚ Czech Republic‚ August 18−22‚ 2014. Vol. 263 of Frontiers in Artificial Intelligence and Applications. Pages 561−566. IOS Press. August, 2014.
Details about Probabilistic Preference Logic Networks | BibTeX data for Probabilistic Preference Logic Networks | Link to Probabilistic Preference Logic Networks
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[256]
Probabilistic Reasoning about Actions in Nonmonotonic Causal Theories
Thomas Eiter and Thomas Lukasiewicz
In Christopher Meek and Uffe Kjærulff, editors, Proceedings of the 19th Conference in Uncertainty in Artificial Intelligence‚ UAI 2003‚ Acapulco‚ Mexico‚ August 7−10‚ 2003. Pages 192−199. Morgan Kaufmann. 2003.
Details about Probabilistic Reasoning about Actions in Nonmonotonic Causal Theories | BibTeX data for Probabilistic Reasoning about Actions in Nonmonotonic Causal Theories | Link to Probabilistic Reasoning about Actions in Nonmonotonic Causal Theories
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[257]
Probabilistic and Truth−Functional Many−Valued Logic Programming
Thomas Lukasiewicz
In Proceedings of the 29th IEEE International Symposium on Multiple−Valued Logic‚ ISMVL 1999‚ Freiburg‚ Germany‚ May 20−22‚ 1999. Pages 236−241. IEEE Computer Society. 1999.
Details about Probabilistic and Truth−Functional Many−Valued Logic Programming | BibTeX data for Probabilistic and Truth−Functional Many−Valued Logic Programming | Link to Probabilistic and Truth−Functional Many−Valued Logic Programming
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[258]
Proceedings of the 10th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2014‚ Riva del Garda‚ Italy‚ October 19−20‚ 2014
Fernando Bobillo‚ Rommel N. Carvalho‚ Davide Ceolin‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Trevor Martin‚ Matthias Nickles‚ Michael Pool‚ Tom De Nies‚ Olaf Hartig‚ Paul Groth and Stephen Marsh, editors
Vol. 1259 of CEUR Workshop Proceedings. CEUR−WS.org. 2014.
Details about Proceedings of the 10th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2014‚ Riva del Garda‚ Italy‚ October 19−20‚ 2014 | BibTeX data for Proceedings of the 10th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2014‚ Riva del Garda‚ Italy‚ October 19−20‚ 2014 | Link to Proceedings of the 10th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2014‚ Riva del Garda‚ Italy‚ October 19−20‚ 2014
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[259]
Proceedings of the 11th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2015‚ Bethlehem‚ USA‚ October 12‚ 2015
Fernando Bobillo‚ Rommel N. Carvalho‚ Davide Ceolin‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Trevor P. Martin‚ Matthias Nickles and Michael Pool, editors
Vol. 1479 of CEUR Workshop Proceedings. CEUR−WS.org. 2015.
Details about Proceedings of the 11th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2015‚ Bethlehem‚ USA‚ October 12‚ 2015 | BibTeX data for Proceedings of the 11th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2015‚ Bethlehem‚ USA‚ October 12‚ 2015 | Link to Proceedings of the 11th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2015‚ Bethlehem‚ USA‚ October 12‚ 2015
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[260]
Proceedings of the 1st International Workshop on Uncertainty in Description Logics‚ UniDL 2010‚ Edinburgh‚ UK‚ July 20‚ 2010
Thomas Lukasiewicz‚ Rafael Peñaloza and Anni−Yasmin Turhan, editors
Vol. 613 of CEUR Workshop Proceedings. CEUR−WS.org. 2010.
Details about Proceedings of the 1st International Workshop on Uncertainty in Description Logics‚ UniDL 2010‚ Edinburgh‚ UK‚ July 20‚ 2010 | BibTeX data for Proceedings of the 1st International Workshop on Uncertainty in Description Logics‚ UniDL 2010‚ Edinburgh‚ UK‚ July 20‚ 2010 | Link to Proceedings of the 1st International Workshop on Uncertainty in Description Logics‚ UniDL 2010‚ Edinburgh‚ UK‚ July 20‚ 2010
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[261]
Proceedings of the 1st Workshop on Logics for Reasoning about Preferences‚ Uncertainty‚ and Vagueness‚ PRUV 2014‚ Vienna‚ Austria‚ July 23−24‚ 2014
Thomas Lukasiewicz‚ Rafael Peñaloza and Anni−Yasmin Turhan, editors
Vol. 1205 of CEUR Workshop Proceedings. CEUR−WS.org. 2014.
Details about Proceedings of the 1st Workshop on Logics for Reasoning about Preferences‚ Uncertainty‚ and Vagueness‚ PRUV 2014‚ Vienna‚ Austria‚ July 23−24‚ 2014 | BibTeX data for Proceedings of the 1st Workshop on Logics for Reasoning about Preferences‚ Uncertainty‚ and Vagueness‚ PRUV 2014‚ Vienna‚ Austria‚ July 23−24‚ 2014 | Link to Proceedings of the 1st Workshop on Logics for Reasoning about Preferences‚ Uncertainty‚ and Vagueness‚ PRUV 2014‚ Vienna‚ Austria‚ July 23−24‚ 2014
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[262]
Proceedings of the 2nd International Conference on Scalable Uncertainty Management‚ SUM 2008‚ Naples‚ Italy‚ October 1−3‚ 2008
Sergio Greco and Thomas Lukasiewicz, editors
Vol. 5291 of Lecture Notes in Computer Science. Springer. 2008.
Details about Proceedings of the 2nd International Conference on Scalable Uncertainty Management‚ SUM 2008‚ Naples‚ Italy‚ October 1−3‚ 2008 | BibTeX data for Proceedings of the 2nd International Conference on Scalable Uncertainty Management‚ SUM 2008‚ Naples‚ Italy‚ October 1−3‚ 2008 | Link to Proceedings of the 2nd International Conference on Scalable Uncertainty Management‚ SUM 2008‚ Naples‚ Italy‚ October 1−3‚ 2008
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[263]
Proceedings of the 2nd Workshop on Logics for Reasoning about Preferences‚ Uncertainty‚ and Vagueness‚ co−located with the 9th International Joint Conference on Automated Reasoning‚ PRUV@IJCAR 2018‚ Oxford‚ UK‚ July 19‚ 2018
Thomas Lukasiewicz‚ Rafael Peñaloza and Anni−Yasmin Turhan
Vol. 2157 of CEUR Workshop Proceedings. CEUR−WS.org. July, 2018.
Details about Proceedings of the 2nd Workshop on Logics for Reasoning about Preferences‚ Uncertainty‚ and Vagueness‚ co−located with the 9th International Joint Conference on Automated Reasoning‚ PRUV@IJCAR 2018‚ Oxford‚ UK‚ July 19‚ 2018 | BibTeX data for Proceedings of the 2nd Workshop on Logics for Reasoning about Preferences‚ Uncertainty‚ and Vagueness‚ co−located with the 9th International Joint Conference on Automated Reasoning‚ PRUV@IJCAR 2018‚ Oxford‚ UK‚ July 19‚ 2018 | Link to Proceedings of the 2nd Workshop on Logics for Reasoning about Preferences‚ Uncertainty‚ and Vagueness‚ co−located with the 9th International Joint Conference on Automated Reasoning‚ PRUV@IJCAR 2018‚ Oxford‚ UK‚ July 19‚ 2018
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[264]
Proceedings of the 2nd Workshop on Semantic Personalized Information Management: Retrieval and Recommendation‚ SPIM 2011‚ Bonn‚ Germany‚ October 24‚ 2011
Marco de Gemmis‚ Ernesto William De Luca‚ Tommaso Di Noia‚ Aldo Gangemi‚ Michael Hausenblas‚ Pasquale Lops‚ Thomas Lukasiewicz‚ Till Plumbaum and Giovanni Semeraro, editors
Vol. 781 of CEUR Workshop Proceedings. CEUR−WS.org. 2011.
Details about Proceedings of the 2nd Workshop on Semantic Personalized Information Management: Retrieval and Recommendation‚ SPIM 2011‚ Bonn‚ Germany‚ October 24‚ 2011 | BibTeX data for Proceedings of the 2nd Workshop on Semantic Personalized Information Management: Retrieval and Recommendation‚ SPIM 2011‚ Bonn‚ Germany‚ October 24‚ 2011 | Link to Proceedings of the 2nd Workshop on Semantic Personalized Information Management: Retrieval and Recommendation‚ SPIM 2011‚ Bonn‚ Germany‚ October 24‚ 2011
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[265]
Proceedings of the 3rd ISWC Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2007‚ Busan‚ Korea‚ November 12‚ 2007
Fernando Bobillo‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Francis Fung‚ Thomas Lukasiewicz‚ Trevor Martin‚ Matthias Nickles‚ Yun Peng‚ Michael Pool‚ Pavel Smrz and Peter Vojtás, editors
Vol. 327 of CEUR Workshop Proceedings. CEUR−WS.org. 2008.
Details about Proceedings of the 3rd ISWC Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2007‚ Busan‚ Korea‚ November 12‚ 2007 | BibTeX data for Proceedings of the 3rd ISWC Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2007‚ Busan‚ Korea‚ November 12‚ 2007 | Link to Proceedings of the 3rd ISWC Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2007‚ Busan‚ Korea‚ November 12‚ 2007
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[266]
Proceedings of the 4th International Conference on Web Reasoning and Rule Systems‚ RR 2010‚ Bressanone/Brixen‚ Italy‚ September 22−24‚ 2010
Pascal Hitzler and Thomas Lukasiewicz, editors
Vol. 6333 of Lecture Notes in Computer Science. Springer. 2010.
Details about Proceedings of the 4th International Conference on Web Reasoning and Rule Systems‚ RR 2010‚ Bressanone/Brixen‚ Italy‚ September 22−24‚ 2010 | BibTeX data for Proceedings of the 4th International Conference on Web Reasoning and Rule Systems‚ RR 2010‚ Bressanone/Brixen‚ Italy‚ September 22−24‚ 2010 | Link to Proceedings of the 4th International Conference on Web Reasoning and Rule Systems‚ RR 2010‚ Bressanone/Brixen‚ Italy‚ September 22−24‚ 2010
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[267]
Proceedings of the 4th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2008‚ Karlsruhe‚ Germany‚ October 26‚ 2008
Fernando Bobillo‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Trevor P. Martin‚ Matthias Nickles‚ Michael Pool and Pavel Smrz, editors
Vol. 423 of CEUR Workshop Proceedings. CEUR−WS.org. 2008.
Details about Proceedings of the 4th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2008‚ Karlsruhe‚ Germany‚ October 26‚ 2008 | BibTeX data for Proceedings of the 4th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2008‚ Karlsruhe‚ Germany‚ October 26‚ 2008 | Link to Proceedings of the 4th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2008‚ Karlsruhe‚ Germany‚ October 26‚ 2008
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[268]
Proceedings of the 5th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2009‚ Washington DC‚ USA‚ October 26‚ 2009
Fernando Bobillo‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Trevor Martin‚ Matthias Nickles‚ Michael Pool and Pavel Smrz, editors
Vol. 527 of CEUR Workshop Proceedings. CEUR−WS.org. 2009.
Details about Proceedings of the 5th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2009‚ Washington DC‚ USA‚ October 26‚ 2009 | BibTeX data for Proceedings of the 5th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2009‚ Washington DC‚ USA‚ October 26‚ 2009 | Link to Proceedings of the 5th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2009‚ Washington DC‚ USA‚ October 26‚ 2009
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[269]
Proceedings of the 6th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2010‚ Shanghai‚ China‚ November 7‚ 2010
Fernando Bobillo‚ Rommel N. Carvalho‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Trevor Martin‚ Matthias Nickles and Michael Pool, editors
Vol. 654 of CEUR Workshop Proceedings. CEUR−WS.org. 2010.
Details about Proceedings of the 6th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2010‚ Shanghai‚ China‚ November 7‚ 2010 | BibTeX data for Proceedings of the 6th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2010‚ Shanghai‚ China‚ November 7‚ 2010 | Link to Proceedings of the 6th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2010‚ Shanghai‚ China‚ November 7‚ 2010
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[270]
Proceedings of the 7th International Symposium on the Foundations of Information and Knowledge Systems‚ FoIKS 2012‚ Kiel‚ Germany‚ March 5−9‚ 2012
Thomas Lukasiewicz and Attila Sali, editors
Vol. 7153 of Lecture Notes in Computer Science. Springer. 2012.
Details about Proceedings of the 7th International Symposium on the Foundations of Information and Knowledge Systems‚ FoIKS 2012‚ Kiel‚ Germany‚ March 5−9‚ 2012 | BibTeX data for Proceedings of the 7th International Symposium on the Foundations of Information and Knowledge Systems‚ FoIKS 2012‚ Kiel‚ Germany‚ March 5−9‚ 2012 | Link to Proceedings of the 7th International Symposium on the Foundations of Information and Knowledge Systems‚ FoIKS 2012‚ Kiel‚ Germany‚ March 5−9‚ 2012
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[271]
Proceedings of the 7th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2011‚ Bonn‚ Germany‚ October 23‚ 2011
Fernando Bobillo‚ Rommel N. Carvalho‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Thomas Lukasiewicz‚ Trevor Martin and Matthias Nickles, editors
Vol. 778 of CEUR Workshop Proceedings. CEUR−WS.org. 2011.
Details about Proceedings of the 7th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2011‚ Bonn‚ Germany‚ October 23‚ 2011 | BibTeX data for Proceedings of the 7th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2011‚ Bonn‚ Germany‚ October 23‚ 2011 | Link to Proceedings of the 7th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2011‚ Bonn‚ Germany‚ October 23‚ 2011
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[272]
Proceedings of the 8th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2012‚ Boston‚ USA‚ November 11‚ 2012
Fernando Bobillo‚ Rommel N. Carvalho‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Trevor Martin‚ Matthias Nickles and Michael Pool, editors
Vol. 900 of CEUR Workshop Proceedings. CEUR−WS.org. 2012.
Details about Proceedings of the 8th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2012‚ Boston‚ USA‚ November 11‚ 2012 | BibTeX data for Proceedings of the 8th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2012‚ Boston‚ USA‚ November 11‚ 2012 | Link to Proceedings of the 8th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2012‚ Boston‚ USA‚ November 11‚ 2012
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[273]
Proceedings of the 9th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2013‚ Sydney‚ Australia‚ October 21‚ 2013
Fernando Bobillo‚ Rommel N. Carvalho‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Trevor Martin‚ Matthias Nickles and Michael Pool, editors
Vol. 1073 of CEUR Workshop Proceedings. CEUR−WS.org. 2013.
Details about Proceedings of the 9th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2013‚ Sydney‚ Australia‚ October 21‚ 2013 | BibTeX data for Proceedings of the 9th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2013‚ Sydney‚ Australia‚ October 21‚ 2013 | Link to Proceedings of the 9th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2013‚ Sydney‚ Australia‚ October 21‚ 2013
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[274]
Proceedings of the International Workshop on Semantic Technologies meet Recommender Systems & Big Data‚ SeRSy 2012‚ Boston‚ USA‚ November 11‚ 2012
Marco de Gemmis‚ Tommaso Di Noia‚ Pasquale Lops‚ Thomas Lukasiewicz and Giovanni Semeraro, editors
Vol. 919 of CEUR Workshop Proceedings. CEUR−WS.org. 2012.
Details about Proceedings of the International Workshop on Semantic Technologies meet Recommender Systems & Big Data‚ SeRSy 2012‚ Boston‚ USA‚ November 11‚ 2012 | BibTeX data for Proceedings of the International Workshop on Semantic Technologies meet Recommender Systems & Big Data‚ SeRSy 2012‚ Boston‚ USA‚ November 11‚ 2012 | Link to Proceedings of the International Workshop on Semantic Technologies meet Recommender Systems & Big Data‚ SeRSy 2012‚ Boston‚ USA‚ November 11‚ 2012
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[275]
Qualitative and Probabilistic Uncertainty in Reasoning about Actions with Sensing
Luca Iocchi‚ Thomas Lukasiewicz‚ Daniele Nardi and Riccardo Rosati
In James P. Delgrande and Torsten Schaub, editors, Proceedings of the 10th International Workshop on Non−Monotonic Reasoning‚ NMR 2004‚ Whistler‚ Canada‚ June 6−8‚ 2004. Pages 240−248. 2004.
Details about Qualitative and Probabilistic Uncertainty in Reasoning about Actions with Sensing | BibTeX data for Qualitative and Probabilistic Uncertainty in Reasoning about Actions with Sensing | Download (pdf) of Qualitative and Probabilistic Uncertainty in Reasoning about Actions with Sensing
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[276]
Query Answer Explanations under Existential Rules
İsmail İlkan Ceylan‚ Thomas Lukasiewicz‚ Enrico Malizia and Andrius Vaicenavicius
In Giuseppe Amato‚ Valentina Bartalesi‚ Devis Bianchini‚ Claudio Gennaro and Riccardo Torlone, editors, Proceedings of the 30th Italian Symposium on Advanced Database Systems‚ SEBD 2022‚ Tirrenia (PI)‚ Italy‚ June 19−22‚ 2022. Vol. 3194 of CEUR Workshop Proceedings. Pages 481–488. CEUR−WS.org. 2022.
Details about Query Answer Explanations under Existential Rules | BibTeX data for Query Answer Explanations under Existential Rules | Download (pdf) of Query Answer Explanations under Existential Rules
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[277]
Query Answering in Datalog+⁄− Ontologies under Group Preferences and Probabilistic Uncertainty
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Oana Tifrea−Marciuska
In Quan Z. Sheng and Jesper Kjeldskov, editors, Proceedings of the 2nd International Workshop on Data Management in the Social Semantic Web‚ DMSSW 2013‚ Aalborg‚ Denmark‚ July 8‚ 2013. Vol. 8295 of Lecture Notes in Computer Science. Pages 192−206. Springer. 2013.
Details about Query Answering in Datalog+⁄− Ontologies under Group Preferences and Probabilistic Uncertainty | BibTeX data for Query Answering in Datalog+⁄− Ontologies under Group Preferences and Probabilistic Uncertainty | Link to Query Answering in Datalog+⁄− Ontologies under Group Preferences and Probabilistic Uncertainty
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[278]
Query Answering in Ontologies Under Preference Rankings
İsmail İlkan Ceylan‚ Thomas Lukasiewicz‚ Rafael Peñaloza and Oana Tifrea−Marciuska
In Carles Sierra, editor, Proceedings of the 26th International Joint Conference on Artificial Intelligence‚ IJCAI 2017‚ Melbourne‚ Australia‚ August 19−25‚ 2017. Pages 943–949. IJCAI/AAAI Press. August, 2017.
Details about Query Answering in Ontologies Under Preference Rankings | BibTeX data for Query Answering in Ontologies Under Preference Rankings | Download (pdf) of Query Answering in Ontologies Under Preference Rankings
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[279]
Query Answering in Probabilistic Datalog+⁄− Ontologies under Group Preferences
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Oana Tifrea−Marciuska
In Vijay Raghavan‚ Xiaolin Hu‚ Churn−Jung and Liau Jan Treur, editors, Proceedings of the 2013 IEEE/WIC/ACM International Conferences on Web Intelligence‚ WI 2013‚ Atlanta‚ GA‚ USA‚ November 17−20‚ 2013. Pages 171−178. IEEE Computer Society. 2013.
Details about Query Answering in Probabilistic Datalog+⁄− Ontologies under Group Preferences | BibTeX data for Query Answering in Probabilistic Datalog+⁄− Ontologies under Group Preferences | Link to Query Answering in Probabilistic Datalog+⁄− Ontologies under Group Preferences
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[280]
Query Answering under Probabilistic Uncertainty in Datalog+⁄− Ontologies
Georg Gottlob‚ Thomas Lukasiewicz‚ Maria Vanina Martinez and Gerardo I. Simari
In Annals of Mathematics and Artificial Intelligence. Vol. 69. No. 1. Pages 37−72. September, 2013.
Details about Query Answering under Probabilistic Uncertainty in Datalog+⁄− Ontologies | BibTeX data for Query Answering under Probabilistic Uncertainty in Datalog+⁄− Ontologies | Link to Query Answering under Probabilistic Uncertainty in Datalog+⁄− Ontologies
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[281]
RIRGAN: An end−to−end lightweight multi−task learning method for brain MRI super−resolution and denoising
Miao Yu‚ Miaomiao Guo‚ Shuai Zhang‚ Yuefu Zhan‚ Mingkang Zhao‚ Thomas Lukasiewicz and Zhenghua Xu
In Computers in Biology and Medicine. Vol. 167. Pages 107632. 2023.
Details about RIRGAN: An end−to−end lightweight multi−task learning method for brain MRI super−resolution and denoising | BibTeX data for RIRGAN: An end−to−end lightweight multi−task learning method for brain MRI super−resolution and denoising | Link to RIRGAN: An end−to−end lightweight multi−task learning method for brain MRI super−resolution and denoising
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[282]
ROAD−R: The Autonomous Driving Dataset with Logical Requirements
Eleonora Giunchiglia‚ Mihaela Catalina Stoian‚ Salman Khan‚ Fabio Cuzzolin and Thomas Lukasiewicz
In Machine Learning. May, 2023.
Details about ROAD−R: The Autonomous Driving Dataset with Logical Requirements | BibTeX data for ROAD−R: The Autonomous Driving Dataset with Logical Requirements | Link to ROAD−R: The Autonomous Driving Dataset with Logical Requirements
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[283]
RSG: A Simple yet Effective Module for Learning Imbalanced Datasets
Jianfeng Wang‚ Thomas Lukasiewicz‚ Xiaolin Hu‚ Jianfei Cai and Zhenghua Xu
In Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition‚ CVPR 2021‚ Virtual‚ June 19–25‚ 2021. June, 2021.
Details about RSG: A Simple yet Effective Module for Learning Imbalanced Datasets | BibTeX data for RSG: A Simple yet Effective Module for Learning Imbalanced Datasets | Link to RSG: A Simple yet Effective Module for Learning Imbalanced Datasets
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[284]
Ranking Answers to Datalog+⁄− Ontologies based on Trust and Reliability of Subjective Reports
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Cristian Molinaro‚ Livia Predoiu and Gerardo I. Simari
In Christoph Beierle‚ Gerhard Brewka and Matthias Thimm:, editors, Computational Models of Rationality: Essays Dedicated to Gabriele Kern−Isberner on the Occasion of Her 60th Birthday. Vol. 29 of Tributes. Pages 175−192. College Publications. January, 2016.
Details about Ranking Answers to Datalog+⁄− Ontologies based on Trust and Reliability of Subjective Reports | BibTeX data for Ranking Answers to Datalog+⁄− Ontologies based on Trust and Reliability of Subjective Reports
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[285]
Rationalizing Predictions by Adversarial Information Calibration
Lei Sha‚ Oana−Maria Camburu and Thomas Lukasiewicz
In Artificial Intelligence. Vol. 315. Pages 103828. February, 2023.
Details about Rationalizing Predictions by Adversarial Information Calibration | BibTeX data for Rationalizing Predictions by Adversarial Information Calibration | Link to Rationalizing Predictions by Adversarial Information Calibration
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[286]
Reasoning about Actions with Sensing under Qualitative and Probabilistic Uncertainty
Luca Iocchi‚ Thomas Lukasiewicz‚ Daniele Nardi and Riccardo Rosati
In Ramon López de Mántaras and Lorenza Saitta, editors, Proceedings of the 16th European Conference on Artificial Intelligence‚ ECAI 2004‚ Valencia‚ Spain‚ August 22−27‚ 2004. Pages 818−822. IOS Press. 2004.
Details about Reasoning about Actions with Sensing under Qualitative and Probabilistic Uncertainty | BibTeX data for Reasoning about Actions with Sensing under Qualitative and Probabilistic Uncertainty | Download (pdf) of Reasoning about Actions with Sensing under Qualitative and Probabilistic Uncertainty
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[287]
Reasoning about Actions with Sensing under Qualitative and Probabilistic Uncertainty
Luca Iocchi‚ Thomas Lukasiewicz‚ Daniele Nardi and Riccardo Rosati
In ACM Transactions on Computational Logic (TOCL). Vol. 10. No. 1. Pages 5:1–5:41. January, 2009.
Details about Reasoning about Actions with Sensing under Qualitative and Probabilistic Uncertainty | BibTeX data for Reasoning about Actions with Sensing under Qualitative and Probabilistic Uncertainty | Link to Reasoning about Actions with Sensing under Qualitative and Probabilistic Uncertainty
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[288]
Reasoning with DL−Based CP−Nets
Tommaso Di Noia‚ Thomas Lukasiewicz and Gerardo I. Simari
In Thomas Eiter‚ Birte Glimm‚ Yevgeny Kazakov and Markus Krötzsch, editors, Proceedings of the 26th International Workshop on Description Logics‚ DL 2013‚ Ulm‚ Germany‚ July 23−26‚ 2013. Vol. 1014 of CEUR Workshop Proceedings. Pages 640−651. CEUR−WS.org. 2013.
Details about Reasoning with DL−Based CP−Nets | BibTeX data for Reasoning with DL−Based CP−Nets | Download (pdf) of Reasoning with DL−Based CP−Nets
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[289]
Reasoning with Imprecise Probabilities
Andrés Cano‚ Fabio Gagliardi Cozman and Thomas Lukasiewicz
In International Journal of Approximate Reasoning. Vol. 44. No. 3. Pages 197–199. March, 2007.
Details about Reasoning with Imprecise Probabilities | BibTeX data for Reasoning with Imprecise Probabilities | Link to Reasoning with Imprecise Probabilities
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[290]
Reasoning with Semantic−Enabled Qualitative Preferences
Tommaso Di Noia‚ Thomas Lukasiewicz and Gerardo I. Simari
In V. S. Subrahmanian W. Liu and J. Wijsen, editors, Proceedings of the 7th International Conference on Scalable Uncertainty Management‚ SUM 2013‚ Washington DC‚ USA‚ September 16−18‚ 2013. Vol. 8078 of Lecture Notes in Computer Science. Pages 374−386. Springer. 2013.
Details about Reasoning with Semantic−Enabled Qualitative Preferences | BibTeX data for Reasoning with Semantic−Enabled Qualitative Preferences | Link to Reasoning with Semantic−Enabled Qualitative Preferences
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[291]
Recent Advances in Querying Probabilistic Knowledge Bases
Stefan Borgwardt‚ İsmail İlkan Ceylan and Thomas Lukasiewicz
In Jérôme Lang, editor, Proceedings of the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence‚ IJCAI−ECAI 2018‚ Stockholm‚ Sweden‚ July 13−19‚ 2018. Pages 5420−5426. IJCAI/AAAI Press. July, 2018.
Details about Recent Advances in Querying Probabilistic Knowledge Bases | BibTeX data for Recent Advances in Querying Probabilistic Knowledge Bases | Link to Recent Advances in Querying Probabilistic Knowledge Bases
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[292]
Recurrent predictive coding models for associative memory employing covariance learning
Mufeng Tang‚ Tommaso Salvatori‚ Beren Millidge‚ Yuhang Song‚ Thomas Lukasiewicz and Rafal Bogacz
In PLOS Computational Biology. Vol. 19. No. 4. Pages e1010719. April, 2023.
Details about Recurrent predictive coding models for associative memory employing covariance learning | BibTeX data for Recurrent predictive coding models for associative memory employing covariance learning | Link to Recurrent predictive coding models for associative memory employing covariance learning
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[293]
Relational Markov Games
Alberto Finzi and Thomas Lukasiewicz
In José Júlio Alferes and João Alexandre Leite, editors, Proceedings of the 9th European Conference on Logics in Artificial Intelligence‚ JELIA 2004‚ Lisbon‚ Portugal‚ September 27−30‚ 2004. Vol. 3229 of Lecture Notes in Computer Science. Pages 320−333. Springer. 2004.
Details about Relational Markov Games | BibTeX data for Relational Markov Games | Link to Relational Markov Games
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[294]
Representing Ontology Mappings with Probabilistic Description Logics Programs
Andrea Calì‚ Thomas Lukasiewicz‚ Livia Predoiu and Heiner Stuckenschmidt
In Salvatore Gaglio‚ Ignazio Infantino and Domenico Saccà, editors, Proceedings of the 16th Italian Symposium on Advanced Database Systems‚ SEBD 2008‚ Mondello‚ Italy‚ June 22−25‚ 2008. Pages 438−445. 2008.
Details about Representing Ontology Mappings with Probabilistic Description Logics Programs | BibTeX data for Representing Ontology Mappings with Probabilistic Description Logics Programs | Download (pdf) of Representing Ontology Mappings with Probabilistic Description Logics Programs
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[295]
Representing Uncertain Concepts in Rough Description Logics via Contextual Indiscernibility Relations
Nicola Fanizzi‚ Claudia d'Amato‚ Floriana Esposito and Thomas Lukasiewicz
In Fernando Bobillo‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Trevor P. Martin‚ Matthias Nickles‚ Michael Pool and Pavel Smrz, editors, Proceedings of the 4th International Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2008‚ Karlsruhe‚ Germany‚ October 26‚ 2008. Vol. 423 of CEUR Workshop Proceedings. CEUR−WS.org. 2008.
Details about Representing Uncertain Concepts in Rough Description Logics via Contextual Indiscernibility Relations | BibTeX data for Representing Uncertain Concepts in Rough Description Logics via Contextual Indiscernibility Relations | Download (pdf) of Representing Uncertain Concepts in Rough Description Logics via Contextual Indiscernibility Relations
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[296]
Representing Uncertain Concepts in Rough Description Logics via Contextual Indiscernibility Relations
Claudia d'Amato‚ Nicola Fanizzi‚ Floriana Esposito and Thomas Lukasiewicz
In Fernando Bobillo‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Matthias Nickles and Michael Pool, editors, Uncertainty Reasoning for the Semantic Web II‚ International Workshops URSW 2008−2010‚ Held at ISWC‚ and UniDL 2010‚ Held at FLoC‚ Revised Selected Papers. Vol. 7123 of Lecture Notes in Computer Science. Pages 300−314. Springer. 2013.
Details about Representing Uncertain Concepts in Rough Description Logics via Contextual Indiscernibility Relations | BibTeX data for Representing Uncertain Concepts in Rough Description Logics via Contextual Indiscernibility Relations | Link to Representing Uncertain Concepts in Rough Description Logics via Contextual Indiscernibility Relations
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[297]
Rethinking Bayesian Deep Learning Methods for Semi−Supervised Volumetric Medical Image Segmentation
Jianfeng Wang and Thomas Lukasiewicz
In Proceedings of the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition‚ CVPR 2022‚ New Orleans‚ Louisiana‚ USA‚ June 19–24‚ 2022. Pages 182–190. June, 2022.
Details about Rethinking Bayesian Deep Learning Methods for Semi−Supervised Volumetric Medical Image Segmentation | BibTeX data for Rethinking Bayesian Deep Learning Methods for Semi−Supervised Volumetric Medical Image Segmentation | Link to Rethinking Bayesian Deep Learning Methods for Semi−Supervised Volumetric Medical Image Segmentation
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[298]
Reverse Differentiation via Predictive Coding
Tommaso Salvatori‚ Yuhang Song‚ Zhenghua Xu‚ Thomas Lukasiewicz and Rafal Bogacz
In Proceedings of the 36th AAAI Conference on Artificial Intelligence‚ AAAI 2022‚ Vancouver‚ BC‚ Canada‚ February 22 – March 1‚ 2022. Pages 8150–8158. AAAI Press. February, 2022.
Details about Reverse Differentiation via Predictive Coding | BibTeX data for Reverse Differentiation via Predictive Coding | Link to Reverse Differentiation via Predictive Coding
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[299]
Rule−Based Approaches for Representing Probabilistic Ontology Mappings
Andrea Calì‚ Thomas Lukasiewicz‚ Livia Predoiu and Heiner Stuckenschmidt
In Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Matthias Nickles and Michael Pool, editors, Uncertainty Reasoning for the Semantic Web I‚ ISWC International Workshops‚ URSW 2005−2007‚ Revised Selected and Invited Papers. Vol. 5327 of Lecture Notes in Computer Science. Pages 66−87. Springer. 2008.
Details about Rule−Based Approaches for Representing Probabilistic Ontology Mappings | BibTeX data for Rule−Based Approaches for Representing Probabilistic Ontology Mappings | Link to Rule−Based Approaches for Representing Probabilistic Ontology Mappings
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[300]
Selective Pseudo−Label Clustering
Louis Mahon and Thomas Lukasiewicz
In Proceedings of the 44th German Conference on Artificial Intelligence‚ KI 2021‚ Berlin‚ Germany‚ 2021. Springer. 2021.
Details about Selective Pseudo−Label Clustering | BibTeX data for Selective Pseudo−Label Clustering | Link to Selective Pseudo−Label Clustering
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[301]
Self−Supervised Medical Image Segmentation Using Deep Reinforced Adaptive Masking
Yunxin Liu‚ Gang Xu‚ Thomas Lukasiewicz and Zhenghua Xu
In IEEE Transactions on Medical Imaging. 2024.
In press.
Details about Self−Supervised Medical Image Segmentation Using Deep Reinforced Adaptive Masking | BibTeX data for Self−Supervised Medical Image Segmentation Using Deep Reinforced Adaptive Masking
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[302]
Semantic Search on the Web
Bettina Fazzinga and Thomas Lukasiewicz
In Semantic Web. Vol. 1. No. 1/2. Pages 89–96. December, 2010.
Details about Semantic Search on the Web | BibTeX data for Semantic Search on the Web | Link to Semantic Search on the Web
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[303]
Semantic Techniques for the Web: The REWERSE Perspective
Wlodzimierz Drabent‚ Thomas Eiter‚ Giovambattista Ianni‚ Thomas Krennwallner‚ Thomas Lukasiewicz and Jan Maluszynski
In François Bry and Jan Maluszynski, editors, REWERSE. Vol. 5500 of Lecture Notes in Computer Science. Pages 1−49. Springer. 2009.
Details about Semantic Techniques for the Web: The REWERSE Perspective | BibTeX data for Semantic Techniques for the Web: The REWERSE Perspective | Link to Semantic Techniques for the Web: The REWERSE Perspective
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[304]
Semantic Web Information Management − A Model−Based Perspective
Andrea Calì‚ Georg Gottlob and Thomas Lukasiewicz
In Roberto De Virgilio‚ Fausto Giunchiglia and Letizia Tanca, editors, Semantic Web Information Management. Pages 249−279. Springer. 2009.
Details about Semantic Web Information Management − A Model−Based Perspective | BibTeX data for Semantic Web Information Management − A Model−Based Perspective | Link to Semantic Web Information Management − A Model−Based Perspective
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[305]
Semantic Web Search Based on Ontological Conjunctive Queries
Bettina Fazzinga‚ Giorgio Gianforme‚ Georg Gottlob and Thomas Lukasiewicz
In Sebastian Link and Henri Prade, editors, Proceedings of the 6th International Symposium on the Foundations of Information and Knowledge Systems‚ FoIKS 2010‚ Sofia‚ Bulgaria‚ February 15−19‚ 2010. Vol. 5956 of Lecture Notes in Computer Science. Pages 153−172. Springer. 2010.
Details about Semantic Web Search Based on Ontological Conjunctive Queries | BibTeX data for Semantic Web Search Based on Ontological Conjunctive Queries | Link to Semantic Web Search Based on Ontological Conjunctive Queries
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[306]
Semantic Web Search Based on Ontological Conjunctive Queries
Bettina Fazzinga‚ Giorgio Gianforme‚ Georg Gottlob and Thomas Lukasiewicz
No. RR−11−08. DCS. October, 2011.
Details about Semantic Web Search Based on Ontological Conjunctive Queries | BibTeX data for Semantic Web Search Based on Ontological Conjunctive Queries | Download (pdf) of Semantic Web Search Based on Ontological Conjunctive Queries
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[307]
Semantic Web Search Based on Ontological Conjunctive Queries
Bettina Fazzinga‚ Giorgio Gianforme‚ Georg Gottlob and Thomas Lukasiewicz
In Journal of Web Semantics. Vol. 9. Pages 453−473. December, 2011.
Details about Semantic Web Search Based on Ontological Conjunctive Queries | BibTeX data for Semantic Web Search Based on Ontological Conjunctive Queries | Link to Semantic Web Search Based on Ontological Conjunctive Queries
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[308]
Semantic Web Search and Inductive Reasoning
Claudia d'Amato‚ Nicola Fanizzi‚ Bettina Fazzinga‚ Georg Gottlob and Thomas Lukasiewicz
In Fernando Bobillo‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Matthias Nickles and Michael Pool, editors, Uncertainty Reasoning for the Semantic Web II‚ International Workshops URSW 2008−2010‚ Held at ISWC‚ and UniDL 2010‚ Held at FLoC‚ Revised Selected Papers. Vol. 7123 of Lecture Notes in Computer Science. Pages 237−261. Springer. 2013.
Details about Semantic Web Search and Inductive Reasoning | BibTeX data for Semantic Web Search and Inductive Reasoning | Link to Semantic Web Search and Inductive Reasoning
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[309]
Stable Model Semantics for Guarded Existential Rules and Description Logics
Georg Gottlob‚ André Hernich‚ Clemens Kupke and Thomas Lukasiewicz
In Chitta Baral and Giuseppe De Giacomo, editors, Proceedings of the 14th International Conference on the Principles of Knowledge Representation and Reasoning‚ KR 2014‚ Vienna‚ Austria‚ July 20−24‚ 2014. Pages 258−267. AAAI Press. July, 2014.
Details about Stable Model Semantics for Guarded Existential Rules and Description Logics | BibTeX data for Stable Model Semantics for Guarded Existential Rules and Description Logics | Link to Stable Model Semantics for Guarded Existential Rules and Description Logics
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[310]
Stable Model Semantics for Guarded Existential Rules and Description Logics: Decidability and Complexity
Georg Gottlob‚ André Hernich‚ Clemens Kupke and Thomas Lukasiewicz
In Journal of the ACM. Vol. 68. No. 5. Pages 35:1–87. October, 2021.
Details about Stable Model Semantics for Guarded Existential Rules and Description Logics: Decidability and Complexity | BibTeX data for Stable Model Semantics for Guarded Existential Rules and Description Logics: Decidability and Complexity | Link to Stable Model Semantics for Guarded Existential Rules and Description Logics: Decidability and Complexity
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[311]
Stratified Probabilistic Description Logic Programs
Thomas Lukasiewicz
In Paulo Cesar G. da Costa‚ Kathryn B. Laskey‚ Kenneth J. Laskey and Michael Pool, editors, Proceedings of the ISWC Workshop on Uncertainty Reasoning for the Semantic Web‚ URSW 2005‚ Galway‚ Ireland‚ November 7‚ 2005. Pages 87−97. 2005.
Details about Stratified Probabilistic Description Logic Programs | BibTeX data for Stratified Probabilistic Description Logic Programs | Download (pdf) of Stratified Probabilistic Description Logic Programs
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[312]
Structure−Based Causes and Explanations in the Independent Choice Logic
Alberto Finzi and Thomas Lukasiewicz
In Christopher Meek and Uffe Kjærulff, editors, Proceedings of the 19th Conference in Uncertainty in Artificial Intelligence‚ UAI 2003‚ Acapulco‚ Mexico‚ August 7−10‚ 2003. Pages 225−232. Morgan Kaufmann. 2003.
Details about Structure−Based Causes and Explanations in the Independent Choice Logic | BibTeX data for Structure−Based Causes and Explanations in the Independent Choice Logic | Link to Structure−Based Causes and Explanations in the Independent Choice Logic
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[313]
Syntactically Rich Discriminative Training: An Effective Method for Open Information Extraction
Frank Mtumbuka and Thomas Lukasiewicz
In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing‚ EMNLP 2022‚ Online and in Abu Dhabi‚ December 7–11‚ 2021. Pages 5972–5987. Association for Computational Linguistics. December, 2022.
Details about Syntactically Rich Discriminative Training: An Effective Method for Open Information Extraction | BibTeX data for Syntactically Rich Discriminative Training: An Effective Method for Open Information Extraction | Link to Syntactically Rich Discriminative Training: An Effective Method for Open Information Extraction
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[314]
Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction
Patrick Hohenecker‚ Frank Mtumbuka‚ Vid Kocijan and Thomas Lukasiewicz
In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing‚ EMNLP 2020‚ November 16–20‚ 2020. Pages 8554–8565. Association for Computational Linguistics. November, 2020.
Details about Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction | BibTeX data for Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction | Link to Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction
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[315]
Tag−Aware Personalized Recommendation Using a Deep−Semantic Similarity Model with Negative Sampling
Zhenghua Xu‚ Cheng Chen‚ Thomas Lukasiewicz‚ Yishu Miao and Xiangwu Meng
In Elisa Bertino‚ Fabio Crestani‚ Javed Mostafa‚ Jie Tang‚ Luo Si and Xiaofang Zhou, editors, Proceedings of the 25th ACM International Conference on Information and Knowledge Management‚ CIKM 2016‚ Indianapolis‚ USA‚ October 24−28‚ 2016. Pages 1921−1924. ACM Press. October, 2016.
Details about Tag−Aware Personalized Recommendation Using a Deep−Semantic Similarity Model with Negative Sampling | BibTeX data for Tag−Aware Personalized Recommendation Using a Deep−Semantic Similarity Model with Negative Sampling | Link to Tag−Aware Personalized Recommendation Using a Deep−Semantic Similarity Model with Negative Sampling
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[316]
Tag−Aware Personalized Recommendation Using a Hybrid Deep Model
Zhenghua Xu‚ Thomas Lukasiewicz‚ Cheng Chen‚ Yishu Miao and Xiangwu Meng
In Carles Sierra, editor, Proceedings of the 26th International Joint Conference on Artificial Intelligence‚ IJCAI 2017‚ Melbourne‚ Australia‚ August 19−25‚ 2017. Pages 3196–3202. IJCAI/AAAI Press. August, 2017.
Details about Tag−Aware Personalized Recommendation Using a Hybrid Deep Model | BibTeX data for Tag−Aware Personalized Recommendation Using a Hybrid Deep Model | Download (pdf) of Tag−Aware Personalized Recommendation Using a Hybrid Deep Model
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[317]
Taxonomic and Uncertain Integrity Constraints in Object−Oriented Databases − the TOP Approach
Thomas Lukasiewicz‚ Werner Kießling‚ Gerhard Köstler and Ulrich Güntzer
In Niki Pissinou‚ Avi Silberschatz‚ E. K. Park and Kia Makki, editors, Proceedings of the 4th International Conference on Information and Knowledge Management‚ CIKM 1995‚ Baltimore‚ Maryland‚ USA‚ November 28 − December 2‚ 1995. Pages 241−249. ACM Press. 1995.
Details about Taxonomic and Uncertain Integrity Constraints in Object−Oriented Databases − the TOP Approach | BibTeX data for Taxonomic and Uncertain Integrity Constraints in Object−Oriented Databases − the TOP Approach | Link to Taxonomic and Uncertain Integrity Constraints in Object−Oriented Databases − the TOP Approach
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[318]
Team Programming in Golog under Partial Observability
Alessandro Farinelli‚ Alberto Finzi and Thomas Lukasiewicz
In Manuela M. Veloso, editor, Proceedings of the 20th International Joint Conference on Artificial Intelligence‚ IJCAI 2007‚ Hyderabad‚ India‚ January 6−12‚ 2007. Pages 2097−2102. 2007.
Details about Team Programming in Golog under Partial Observability | BibTeX data for Team Programming in Golog under Partial Observability | Download (pdf) of Team Programming in Golog under Partial Observability
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[319]
Temporal Probabilistic Object Bases
Veronica Biazzo‚ Rosalba Giugno‚ Thomas Lukasiewicz and V. S. Subrahmanian
In IEEE Transactions on Knowledge and Data Engineering (TKDE). Vol. 15. No. 4. Pages 921–939. 2003.
Details about Temporal Probabilistic Object Bases | BibTeX data for Temporal Probabilistic Object Bases | Link to Temporal Probabilistic Object Bases
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[320]
Text attribute control via closed−loop disentanglement
Lei Sha and Thomas Lukasiewicz
In Transactions of the Association for Computational Linguistics (TACL). 2023.
Accepted for publication
Details about Text attribute control via closed−loop disentanglement | BibTeX data for Text attribute control via closed−loop disentanglement | Link to Text attribute control via closed−loop disentanglement
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[321]
The Defeat of the Winograd Schema Challenge
Vid Kocijan‚ Ernest Davis‚ Thomas Lukasiewicz‚ Gary Marcus and Leora Morgenstern
In Artificial Intelligence. Vol. 325. No. 103971. December, 2023.
Details about The Defeat of the Winograd Schema Challenge | BibTeX data for The Defeat of the Winograd Schema Challenge | Link to The Defeat of the Winograd Schema Challenge
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[322]
The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias−Measuring Datasets
Vid Kocijan‚ Oana−Maria Camburu and Thomas Lukasiewicz
In Kevin Leyton−Brown and Mausam, editors, Proceedings of the 35th AAAI Conference on Artificial Intelligence‚ AAAI 2021‚ Virtual Conference‚ February 2–9‚ 2021. AAAI Press. 2021.
Details about The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias−Measuring Datasets | BibTeX data for The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias−Measuring Datasets | Link to The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias−Measuring Datasets
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[323]
The IMO Small Challenge: First IMO Dataset for LLMs
Simon Frieder‚ Mirek Olšák‚ Julius Berner and Thomas Lukasiewicz
In Proceedings of the 12th International Conference on Learning Representations‚ ICLR 2024‚ Tiny Papers Track‚ Vienna‚ Austria‚ 7–11 May 2024. May, 2024.
Details about The IMO Small Challenge: First IMO Dataset for LLMs | BibTeX data for The IMO Small Challenge: First IMO Dataset for LLMs
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[324]
The Surprising Power of Graph Neural Networks with Random Node Initialization
Ralph Abboud‚ İsmail İlkan Ceylan‚ Martin Grohe and Thomas Lukasiewicz
In Proceedings of the 30th International Joint Conference on Artificial Intelligence‚ IJCAI 2021‚ August 21–26‚ 2021. IJCAI. August, 2021.
Details about The Surprising Power of Graph Neural Networks with Random Node Initialization | BibTeX data for The Surprising Power of Graph Neural Networks with Random Node Initialization | Link to The Surprising Power of Graph Neural Networks with Random Node Initialization
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[325]
The TOP Database Model − Taxonomy‚ Object−Orientation and Probability
Werner Kießling‚ Thomas Lukasiewicz‚ Gerhard Köstler and Ulrich Güntzer
In Proceedings of the International Workshop on Uncertainty in Databases and Deductive Systems‚ Ithaca‚ New York‚ USA‚ November 1994. Pages 71−82. 1994.
Details about The TOP Database Model − Taxonomy‚ Object−Orientation and Probability | BibTeX data for The TOP Database Model − Taxonomy‚ Object−Orientation and Probability | Link to The TOP Database Model − Taxonomy‚ Object−Orientation and Probability
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[326]
Tightly Coupled Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web
Thomas Lukasiewicz and Umberto Straccia
In M. Lytras and A. Sheth, editors, Progressive Concepts for Semantic Web Evolution: Applications and Developments. Pages 237−256. Information Science Reference. 2010.
Details about Tightly Coupled Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web | BibTeX data for Tightly Coupled Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web | Link to Tightly Coupled Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web
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[327]
Tightly Coupled Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web
Thomas Lukasiewicz and Umberto Straccia
In International Journal on Semantic Web and Information Systems. Vol. 4. No. 3. Pages 68–89. 2008.
Details about Tightly Coupled Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web | BibTeX data for Tightly Coupled Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web | Link to Tightly Coupled Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web
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[328]
Tightly Coupled Probabilistic Description Logic Programs for the Semantic Web
Andrea Calì‚ Thomas Lukasiewicz‚ Livia Predoiu and Heiner Stuckenschmidt
In Journal on Data Semantics. Vol. 12. Pages 95−130. 2009.
Details about Tightly Coupled Probabilistic Description Logic Programs for the Semantic Web | BibTeX data for Tightly Coupled Probabilistic Description Logic Programs for the Semantic Web | Link to Tightly Coupled Probabilistic Description Logic Programs for the Semantic Web
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[329]
Tightly Integrated Fuzzy Description Logic Programs Under the Answer Set Semantics for the Semantic Web
Thomas Lukasiewicz and Umberto Straccia
In Massimo Marchiori‚ Jeff Z. Pan and Christian de Sainte Marie, editors, Proceedings of the 1st International Conference on Web Reasoning and Rule Systems‚ RR 2007‚ Innsbruck‚ Austria‚ June 7−8‚ 2007. Vol. 4524 of Lecture Notes in Computer Science. Pages 289−298. Springer. 2007.
Details about Tightly Integrated Fuzzy Description Logic Programs Under the Answer Set Semantics for the Semantic Web | BibTeX data for Tightly Integrated Fuzzy Description Logic Programs Under the Answer Set Semantics for the Semantic Web | Link to Tightly Integrated Fuzzy Description Logic Programs Under the Answer Set Semantics for the Semantic Web
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[330]
Tightly Integrated Probabilistic Description Logic Programs for Representing Ontology Mappings
Andrea Calì‚ Thomas Lukasiewicz‚ Livia Predoiu and Heiner Stuckenschmidt
In Sven Hartmann and Gabriele Kern−Isberner, editors, Proceedings of the 5th International Symposium on the Foundations of Information and Knowledge Systems‚ FoIKS 2008‚ Pisa‚ Italy‚ February 11−15‚ 2008. Vol. 4932 of Lecture Notes in Computer Science. Pages 178−198. Springer. 2008.
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[331]
Tightly Integrated Probabilistic Description Logic Programs for Representing Ontology Mappings
Thomas Lukasiewicz‚ Livia Predoiu and Heiner Stuckenschmidt
In Annals of Mathematics and Artificial Intelligence. Vol. 63. No. 3/4. Pages 385−425. December, 2011.
Details about Tightly Integrated Probabilistic Description Logic Programs for Representing Ontology Mappings | BibTeX data for Tightly Integrated Probabilistic Description Logic Programs for Representing Ontology Mappings | Link to Tightly Integrated Probabilistic Description Logic Programs for Representing Ontology Mappings
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[332]
Tightly Integrated Probabilistic Description Logic Programs for the Semantic Web
Andrea Calì and Thomas Lukasiewicz
In Verónica Dahl and Ilkka Niemelä, editors, Proceedings of the 23rd International Conference on Logic Programming‚ ICLP 2007‚ Porto‚ Portugal‚ September 8−13‚ 2007. Vol. 4670 of Lecture Notes in Computer Science. Pages 428−429. Springer. 2007.
Details about Tightly Integrated Probabilistic Description Logic Programs for the Semantic Web | BibTeX data for Tightly Integrated Probabilistic Description Logic Programs for the Semantic Web | Link to Tightly Integrated Probabilistic Description Logic Programs for the Semantic Web
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[333]
Top−k Query Answering in Datalog+/ Ontologies under Subjective Reports
Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Cristian Molinaro‚ Livia Predoiu and Gerardo I. Simari
2013.
Details about Top−k Query Answering in Datalog+/ Ontologies under Subjective Reports | BibTeX data for Top−k Query Answering in Datalog+/ Ontologies under Subjective Reports | Link to Top−k Query Answering in Datalog+/ Ontologies under Subjective Reports
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[334]
Top−k Retrieval in Description Logic Programs Under Vagueness for the Semantic Web
Thomas Lukasiewicz and Umberto Straccia
In Henri Prade and V. S. Subrahmanian, editors, Proceedings of the 1st International Conference on Scalable Uncertainty Management‚ SUM 2007‚ Washington‚ DC‚ USA‚ October 10−12‚ 2007. Vol. 4772 of Lecture Notes in Computer Science. Pages 16−30. Springer. 2007.
Details about Top−k Retrieval in Description Logic Programs Under Vagueness for the Semantic Web | BibTeX data for Top−k Retrieval in Description Logic Programs Under Vagueness for the Semantic Web | Link to Top−k Retrieval in Description Logic Programs Under Vagueness for the Semantic Web
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[335]
Toward Knowledge as a Service (KaaS): Predicting Popularity of Knowledge Services Leveraging Graph Neural Networks
Haozhe Lin‚ Yushun Fan‚ Jia Zhang‚ Bing Bai‚ Zhenghua Xu and Thomas Lukasiewicz
In IEEE Transactions on Services Computing. Vol. 16. No. 1. Pages 642–655. January, 2022.
Details about Toward Knowledge as a Service (KaaS): Predicting Popularity of Knowledge Services Leveraging Graph Neural Networks | BibTeX data for Toward Knowledge as a Service (KaaS): Predicting Popularity of Knowledge Services Leveraging Graph Neural Networks | Link to Toward Knowledge as a Service (KaaS): Predicting Popularity of Knowledge Services Leveraging Graph Neural Networks
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[336]
Tractable Probabilistic Description Logic Programs
Thomas Lukasiewicz
In Henri Prade and V. S. Subrahmanian, editors, Proceedings of the 1st International Conference on Scalable Uncertainty Management‚ SUM 2007‚ Washington‚ DC‚ USA‚ October 10−12‚ 2007. Vol. 4772 of Lecture Notes in Computer Science. Pages 143−156. Springer. 2007.
Details about Tractable Probabilistic Description Logic Programs | BibTeX data for Tractable Probabilistic Description Logic Programs | Link to Tractable Probabilistic Description Logic Programs
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[337]
Tractable Probabilistic Description Logic Programs
Thomas Lukasiewicz and Gerardo I. Simari
In Z. Ma and L. Yan, editors, Advances in Probabilistic Databases for Uncertain Information Management. Vol. 304 of Studies in Fuzziness and Soft Computing. Pages 131−159. Springer. 2013.
Details about Tractable Probabilistic Description Logic Programs | BibTeX data for Tractable Probabilistic Description Logic Programs | Link to Tractable Probabilistic Description Logic Programs
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[338]
Tractable Query Answering over Ontologies with Datalog+⁄−
Andrea Calì‚ Georg Gottlob and Thomas Lukasiewicz
In Bernardo Cuenca Grau‚ Ian Horrocks‚ Boris Motik and Ulrike Sattler, editors, Proceedings of the 22nd International Workshop on Description Logics‚ DL 2009‚ Oxford‚ UK‚ July 27−30‚ 2009. Vol. 477 of CEUR Workshop Proceedings. CEUR−WS.org. 2009.
Details about Tractable Query Answering over Ontologies with Datalog+⁄− | BibTeX data for Tractable Query Answering over Ontologies with Datalog+⁄− | Download (pdf) of Tractable Query Answering over Ontologies with Datalog+⁄−
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[339]
Tractable Reasoning with Bayesian Description Logics
Claudia d'Amato‚ Nicola Fanizzi and Thomas Lukasiewicz
In Sergio Greco and Thomas Lukasiewicz, editors, Proceedings of the 2nd International Conference on Scalable Uncertainty Management‚ SUM 2008‚ Naples‚ Italy‚ October 1−3‚ 2008. Vol. 5291 of Lecture Notes in Computer Science. Pages 146−159. Springer. 2008.
Details about Tractable Reasoning with Bayesian Description Logics | BibTeX data for Tractable Reasoning with Bayesian Description Logics | Link to Tractable Reasoning with Bayesian Description Logics
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[340]
Uncertain Reasoning in Concept Lattices
Thomas Lukasiewicz
In Christine Froidevaux and Jürg Kohlas, editors, Proceedings of the 3rd European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty‚ ECSQARU 1995‚ Fribourg‚ Switzerland‚ July 3−5‚ 1995. Vol. 946 of Lecture Notes in Computer Science. Pages 293−300. Springer. 1995.
Details about Uncertain Reasoning in Concept Lattices | BibTeX data for Uncertain Reasoning in Concept Lattices | Link to Uncertain Reasoning in Concept Lattices
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[341]
Uncertainty Reasoning for the Semantic Web
Thomas Lukasiewicz
In Giovambattista Ianni‚ Domenico Lembo‚ Leopoldo E. Bertossi‚ Wolfgang Faber‚ Birte Glimm‚ Georg Gottlob and Steffen Staab, editors, Reasoning Web. Semantic Interoperability on the Web − 13th International Summer School 2017‚ London‚ UK‚ July 7−11‚ 2017‚ Tutorial Lectures. Vol. 10370 of Lecture Notes in Computer Science. Pages 276–291. Springer. 2017.
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[342]
Uncertainty Reasoning for the Semantic Web
Thomas Lukasiewicz
In Axel Polleres and Terrance Swift, editors, Proceedings of the 3rd International Conference on Web Reasoning and Rule Systems‚ RR 2009‚ Chantilly‚ VA‚ USA‚ October 25−26‚ 2009. Vol. 5837 of Lecture Notes in Computer Science. Pages 26−39. Springer. 2009.
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[343]
Uncertainty Reasoning for the Semantic Web I‚ ISWC International Workshops‚ URSW 2005−2007‚ Revised Selected and Invited Papers
Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Matthias Nickles and Michael Pool, editors
Vol. 5327 of Lecture Notes in Computer Science. Springer. 2008.
Details about Uncertainty Reasoning for the Semantic Web I‚ ISWC International Workshops‚ URSW 2005−2007‚ Revised Selected and Invited Papers | BibTeX data for Uncertainty Reasoning for the Semantic Web I‚ ISWC International Workshops‚ URSW 2005−2007‚ Revised Selected and Invited Papers | Link to Uncertainty Reasoning for the Semantic Web I‚ ISWC International Workshops‚ URSW 2005−2007‚ Revised Selected and Invited Papers
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[344]
Uncertainty Reasoning for the Semantic Web II‚ International Workshops URSW 2008−2010‚ Held at ISWC‚ and UniDL 2010‚ Held at FLoC‚ Revised Selected Papers
Fernando Bobillo‚ Paulo Cesar G. da Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Matthias Nickles and Michael Pool, editors
Vol. 7123 of Lecture Notes in Computer Science. Springer. 2013.
Details about Uncertainty Reasoning for the Semantic Web II‚ International Workshops URSW 2008−2010‚ Held at ISWC‚ and UniDL 2010‚ Held at FLoC‚ Revised Selected Papers | BibTeX data for Uncertainty Reasoning for the Semantic Web II‚ International Workshops URSW 2008−2010‚ Held at ISWC‚ and UniDL 2010‚ Held at FLoC‚ Revised Selected Papers | Link to Uncertainty Reasoning for the Semantic Web II‚ International Workshops URSW 2008−2010‚ Held at ISWC‚ and UniDL 2010‚ Held at FLoC‚ Revised Selected Papers
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[345]
Uncertainty Reasoning for the Semantic Web III‚ International Workshops URSW 2011−2013‚ Held at ISWC‚ Revised Selected Papers
Fernando Bobillo‚ Rommel Carvalho‚ Paulo C. G. Costa‚ Claudia d'Amato‚ Nicola Fanizzi‚ Kathryn B. Laskey‚ Kenneth J. Laskey‚ Thomas Lukasiewicz‚ Matthias Nickles and Michael Pool, editors
Vol. 8816 of Lecture Notes in Computer Science. Springer. 2014.
Details about Uncertainty Reasoning for the Semantic Web III‚ International Workshops URSW 2011−2013‚ Held at ISWC‚ Revised Selected Papers | BibTeX data for Uncertainty Reasoning for the Semantic Web III‚ International Workshops URSW 2011−2013‚ Held at ISWC‚ Revised Selected Papers | Link to Uncertainty Reasoning for the Semantic Web III‚ International Workshops URSW 2011−2013‚ Held at ISWC‚ Revised Selected Papers
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[346]
Uncertainty Representation and Reasoning in the Semantic Web
Paulo C. G. da Costa‚ Kathryn B. Laskey and Thomas Lukasiewicz
In J. Cardoso and M. D. Lytras, editors, Semantic Web Engineering in the Knowledge Society. Pages 315−340. Information Science Reference. October, 2008.
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[347]
Uncertainty in the Semantic Web
Thomas Lukasiewicz
In Lluis Godo and Andrea Pugliese, editors, Proceedings of the 3rd International Conference on Scalable Uncertainty Management‚ SUM 2009‚ Washington‚ DC‚ USA‚ September 28−30‚ 2009. Vol. 5785 of Lecture Notes in Computer Science. Pages 2−11. Springer. 2009.
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[348]
Universal Hopfield Networks: A General Framework for Single−Shot Associative Memory Models
Beren Millidge‚ Tommaso Salvatori‚ Yuhang Song‚ Thomas Lukasiewicz and Rafal Bogacz
In Kamalika Chaudhuri‚ Stefanie Jegelka‚ Le Song‚ Csaba Szepesvari‚ Gang Niu and Sivan Sabato, editors, Proceedings of the 39th International Conference on Machine Learning‚ ICML 2022‚ Baltimore‚ Maryland‚ USA‚ 17−23 July 2022. Vol. 162 of Proceedings of Machine Learning Research. Pages 15561–15583. PMLR. July, 2022.
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[349]
Using Search Strategies and a Description Logic Paradigm with Conditional Preferences for Literature Search
Jörg Schellhase and Thomas Lukasiewicz
In International Journal of Metadata‚ Semantics and Ontologies. Vol. 3. No. 1. Pages 68–83. 2008.
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[350]
Variable−Strength Conditional Preferences for Matchmaking in Description Logics
Thomas Lukasiewicz and Jörg Schellhase
In Patrick Doherty‚ John Mylopoulos and Christopher A. Welty, editors, Proceedings of the 10th International Conference on the Principles of Knowledge Representation and Reasoning‚ KR 2006‚ Lake District‚ UK‚ June 2−5‚ 2006. Pages 164−174. AAAI Press. 2006.
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[351]
Variable−Strength Conditional Preferences for Ranking Objects in Ontologies
Thomas Lukasiewicz and Jörg Schellhase
In York Sure and John Domingue, editors, Proceedings of the 3rd European Semantic Web Conference‚ ESWC 2006‚ Budva‚ Montenegro‚ June 11−14‚ 2006. Vol. 4011 of Lecture Notes in Computer Science. Pages 288−302. Springer. 2006.
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[352]
Variable−Strength Conditional Preferences for Ranking Objects in Ontologies
Thomas Lukasiewicz and Jörg Schellhase
In Journal of Web Semantics. Vol. 5. No. 3. Pages 180–194. September, 2007.
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[353]
Weak Nonmonotonic Probabilistic Logics
Thomas Lukasiewicz
In Didier Dubois‚ Christopher A. Welty and Mary−Anne Williams, editors, Proceedings of the 9th International Conference on the Principles of Knowledge Representation and Reasoning‚ KR 2004‚ Whistler‚ Canada‚ June 2−5‚ 2004. Pages 23−33. AAAI Press. 2004.
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[354]
Weak Nonmonotonic Probabilistic Logics
Thomas Lukasiewicz
In Artificial Intelligence. Vol. 168. No. 1/2. Pages 119–161. October, 2005.
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[355]
Well−Founded Semantics for Description Logic Programs in the Semantic Web
Thomas Eiter‚ Thomas Lukasiewicz‚ Roman Schindlauer and Hans Tompits
In Grigoris Antoniou and Harold Boley, editors, Proceedings of the 3rd International Workshop on Rules and Rule Markup Languages for the Semantic Web‚ RuleML 2004‚ Hiroshima‚ Japan‚ November 8‚ 2004. Vol. 3323 of Lecture Notes in Computer Science. Pages 81−97. Springer. 2004.
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[356]
Well−Founded Semantics for Extended Datalog and Ontological Reasoning
André Hernich‚ Clemens Kupke‚ Thomas Lukasiewicz and Georg Gottlob
In Thomas Eiter‚ Birte Glimm‚ Yevgeny Kazakov and Markus Krötzsch, editors, Proceedings of the 26th International Workshop on Description Logics‚ DL 2013‚ Ulm‚ Germany‚ July 23−26‚ 2013. Vol. 1014 of CEUR Workshop Proceedings. Pages 209−220. CEUR−WS.org. 2013.
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[357]
Well−Founded Semantics for Extended Datalog and Ontological Reasoning
André Hernich‚ Clemens Kupke‚ Thomas Lukasiewicz and Georg Gottlob
In Richard Hull and Wenfei Fan, editors, Proceedings of the 32nd ACM Symposium on Principles of Database Systems‚ PODS 2013‚ New York‚ New York‚ USA‚ June 22−27‚ 2013. Pages 225−236. ACM Press. 2013.
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[358]
Well−founded Semantics for Description Logic Programs in the Semantic Web
Thomas Eiter‚ Giovambattista Ianni‚ Thomas Lukasiewicz and Roman Schindlauer
In ACM Transactions on Computational Logic (TOCL). Vol. 12. No. 2. Pages 11:1–11:41. January, 2011.
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[359]
WikiCREM: A Large Unsupervised Corpus for Co−Reference Resolution
Vid Kocijan‚ Oana−Maria Camburu‚ Ana−Maria Cretu‚ Yordan Yordanov‚ Phil Blunsom and Thomas Lukasiewicz
In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing‚ EMNLP−IJCNLP 2019‚ Hong Kong‚ China‚ November 3–7‚ 2019. November, 2019.
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[360]
e−SNLI: Natural Language Inference with Natural Language Explanations
Oana−Maria Camburu‚ Tim Rocktäschel‚ Thomas Lukasiewicz and Phil Blunsom
In Samy Bengio‚ Hanna Wallach‚ Hugo Larochelle‚ Kristen Grauman‚ Nicolò Cesa−Bianchi and Roman Garnett, editors, Proceedings of the 32nd Annual Conference on Neural Information Processing Systems‚ NeurIPS 2018‚ Montreal‚ Canada‚ December 3−8‚ 2018. Pages 9560–9572. Curran Associates‚ Inc.. December, 2018.
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[361]
e−ViL: A Dataset and Benchmark for Natural Language Explanations in Vision−Language Tasks
Maxime Kayser‚ Oana−Maria Camburu‚ Leonard Salewski‚ Cornelius Emde‚ Virginie Do‚ Zeynep Akata and Thomas Lukasiewicz
In Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision‚ ICCV 2021‚ Virtual Conference‚ October 11–17‚ 2021. October, 2021.
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[362]
μ−Net: Medical image segmentation using efficient and effective deep supervision
Di Yuan‚ Zhenghua Xu‚ Biao Tian‚ Hening Wang‚ Yuefu Zhan and Thomas Lukasiewicz
In Computers in Biology and Medicine. Vol. 160. Pages 106963. June, 2023.
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[363]
ω−Net: Dual Supervised Medical Image Segmentation with Multi−Dimensional Self−Attention and Diversely−Connected Multi−Scale Convolution
Zhenghua Xu‚ Shijie Liu‚ Di Yuan‚ Lei Wang‚ Junyang Chen‚ Thomas Lukasiewicz‚ Zhigang Fu and Rui Zhang
In Neurocomputing. Vol. 500. Pages 177−190. August, 2022.
Details about ω−Net: Dual Supervised Medical Image Segmentation with Multi−Dimensional Self−Attention and Diversely−Connected Multi−Scale Convolution | BibTeX data for ω−Net: Dual Supervised Medical Image Segmentation with Multi−Dimensional Self−Attention and Diversely−Connected Multi−Scale Convolution | Link to ω−Net: Dual Supervised Medical Image Segmentation with Multi−Dimensional Self−Attention and Diversely−Connected Multi−Scale Convolution