Thomas Lukasiewicz
Professor Thomas Lukasiewicz
Themes:
- Artificial Intelligence and Machine Learning
- Data, Knowledge and Action
- Algorithms and Complexity Theory
Completed Projects:
Interests
For more information on Thomas Lukasiewicz and his team, see: Intelligent Systems Lab.
Selected Publications
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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. Vol. 36. No. 2. Pages 2206–2220. February, 2025.
Details about Hybrid Reinforced Medical Report Generation with M−Linear Attention and Repetition Penalty | BibTeX data for Hybrid Reinforced Medical Report Generation with M−Linear Attention and Repetition Penalty | DOI (https://doi.org/10.1109/TNNLS.2023.3343391)
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Training Deep Predictive Coding Networks
Chang Qi‚ Thomas Lukasiewicz and Tommaso Salvatori.
In Proceedings of the ICLR 2025 Workshop on New Frontiers in Associative Memories‚ Singapore‚ 27 April 2025. February, 2025.
Details about Training Deep Predictive Coding Networks | BibTeX data for Training Deep Predictive Coding Networks
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Effective and Efficient Medical Image Segmentation with Hierarchical Context Interaction
Zehua Cheng‚ Di Yuan‚ Wenhu Zhang and Thomas Lukasiewicz
In Proceedings of the Winter Conference on Applications of Computer Vision (WACV). Pages 9378–9387. February, 2025.
Details about Effective and Efficient Medical Image Segmentation with Hierarchical Context Interaction | BibTeX data for Effective and Efficient Medical Image Segmentation with Hierarchical Context Interaction | Link to Effective and Efficient Medical Image Segmentation with Hierarchical Context Interaction