Giovanni de Felice
Interests
I am interested in the applications of Category theory to Natural Language Processing (NLP) and Quantum Computing (QC). In the context of NLP, I have been working on the relationship between Pregroup Grammar and Database Theory with the aim of building structured question-answering algorithms. These models can be implemented using classical and quantum Machine Learning techniques borrowed from the database community. My research in QC is focused at developing graphical formalisms to translate between different models of quantum computation such as Topological, Fermionic, Measurement-Based and Gate-Based Quantum Computing. I enjoy reasoning with diagrams and discussing the role of contextuality in databases, quantum physics and natural language.
Biography
I did my undergrad at Imperial College London in Mathematics and graduated from the MFOCS with a thesis on Hopf algebras in Quantum Computation, supervised by Bob Coecke.
Selected Publications
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Quantum Natural Language Processing on Near−Term Quantum Computers
Konstantinos Meichanetzidis‚ Stefano Gogioso‚ Giovanni De Felice‚ Nicolò Chiappori‚ Alexis Toumi and Bob Coecke
2020.
Details about Quantum Natural Language Processing on Near−Term Quantum Computers | BibTeX data for Quantum Natural Language Processing on Near−Term Quantum Computers | Link to Quantum Natural Language Processing on Near−Term Quantum Computers
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Functorial Question Answering
Giovanni de Felice‚ Konstantinos Meichanetzidis and Alexis Toumi
2019.
Details about Functorial Question Answering | BibTeX data for Functorial Question Answering | Link to Functorial Question Answering
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Towards Compositional Distributional Discourse Analysis
Bob Coecke‚ Giovanni de Felice‚ Dan Marsden and Alexis Toumi
In Electronic Proceedings of Theoretical Computer Science. Vol. 283. Pages 1−12. 2018.
Details about Towards Compositional Distributional Discourse Analysis | BibTeX data for Towards Compositional Distributional Discourse Analysis | DOI (10.4204/EPTCS.283.1) | Link to Towards Compositional Distributional Discourse Analysis