Thomas Feller
From International Center for Computational Logic
M.Sc. Thomas Feller
Research Associate Computational Logic
- thomas.feller@tu-dresden.de
- +49 351 463 42665
- APB 2031
Since October 2018 I am a research assistent and doctoral student at the Institute for Artificial Intelligence in the Computational Logic group. My work revolves around general model theoretic characteristics of decidable knowledge representations in the context of the ERC project "DeciGUT". My academic background is a Master of Science in mathematics with emphasise on algebra and model theory.
Since December 2018 i am also associated doctoral student at the research training group "QuantLA".
Newest Publications
Thomas Feller, Tim Lyon, Piotr Ostropolski-Nalewaja, Sebastian Rudolph
Finite-Cliquewidth Sets of Existential Rules – Toward a General Criterion for Decidable yet Highly Expressive Querying
Proceedings of the 26th International Conference on Database Theory (ICDT 2023), to appear
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Manuel Bodirsky, Thomas Feller, Simon Knäuer, Sebastian Rudolph
On Logics and Homomorphism Closure
Proceedings of the 36th Annual Symposium on Logic in Computer Science (LICS 2021), 1-13, 2021. IEEE
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Frederic Dörband, Thomas Feller, Kevin Stier
Sequentiality of Group-Weighted Tree Automata
In Alberto Leporati, Carlos Martín-Vide, Dana Shapira, Claudio Zandron, eds., Language and Automata Theory and Applications. LATA 2021., volume 12638 of Lecture Notes in Computer Science, 267-278, February 2021. Springer
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Frederic Dörband, Thomas Feller, Kevin Stier
Approximated Determinisation of Weighted Tree Automata
In Alberto Leporati, Carlos Martín-Vide, Dana Shapira, Claudio Zandron, eds., Language and Automata Theory and Applications. LATA 2021., volume 12638 of Lecture Notes in Computer Science, 255-266, February 2021. Springer
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Thomas Feller, Christian Pech, Maja Pech
The classification of homomorphism homogeneous tournaments
European Journal of Combinatorics, 89:103142, October 2020
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Courses
- Research Seminar Logic and AI (SS 2021)
- Research Seminar Logic and AI (WS 2020)
DeciGUT
A Grand Unified Theory of Decidability in Logic-Based Knowledge Representation
