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Conference and Workshop Papers
- 2024
[c5]Parth Padalkar, Natalia Slusarz, Ekaterina Komendantskaya, Gopal Gupta:
A Neurosymbolic Framework for Bias Correction in Convolutional Neural Networks. ICLP Workshops 2024- [c4]Reynald Affeldt
, Alessandro Bruni, Ekaterina Komendantskaya, Natalia Slusarz, Kathrin Stark:
Taming Differentiable Logics with Coq Formalisation. ITP 2024: 4:1-4:19 - 2023
- [c3]Matthew L. Daggitt, Wen Kokke, Ekaterina Komendantskaya, Robert Atkey, Luca Arnaboldi, Natalia Slusarz, Marco Casadio, Ben Coke, Jeonghyeon Lee:
The Vehicle Tutorial: Neural Network Verification with Vehicle. FoMLAS@CAV 2023: 1-5 - [c2]Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart, Kathrin Stark:
Logic of Differentiable Logics: Towards a Uniform Semantics of DL. LPAR 2023: 473-493 - 2022
- [c1]Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart:
Differentiable Logics for Neural Network Training and Verification. NSV/FoMLAS@CAV 2022: 67-77
Data and Artifacts
- 2024
- [d1]Natalia Slusarz, Reynald Affeldt, Alessandro Bruni:
Formalisation of Differentiable Logics in Coq. DROPS Artifacts, 2024
Informal and Other Publications
- 2024
- [i5]Matthew L. Daggitt, Wen Kokke, Robert Atkey, Natalia Slusarz, Luca Arnaboldi, Ekaterina Komendantskaya:
Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programs. CoRR abs/2401.06379 (2024) - [i4]Reynald Affeldt, Alessandro Bruni, Ekaterina Komendantskaya, Natalia Slusarz, Kathrin Stark:
Taming Differentiable Logics with Coq Formalisation. CoRR abs/2403.13700 (2024) - [i3]Parth Padalkar, Natalia Slusarz, Ekaterina Komendantskaya, Gopal Gupta:
A Neurosymbolic Framework for Bias Correction in CNNs. CoRR abs/2405.15886 (2024) - 2023
- [i2]Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart, Kathrin Stark:
Logic of Differentiable Logics: Towards a Uniform Semantics of DL. CoRR abs/2303.10650 (2023) - 2022
- [i1]Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart:
Differentiable Logics for Neural Network Training and Verification. CoRR abs/2207.06741 (2022)
Coauthor Index
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