Natalia Slusarz

According to our database, Natalia Slusarz authored at least 8 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Formalisation of Differentiable Logics in Coq.

Natalia Slusarz, Reynald Affeldt, Alessandro Bruni

Dataset, November, 2024

A Neurosymbolic Framework for Bias Correction in CNNs.

Parth Padalkar, Natalia Slusarz, Ekaterina Komendantskaya, Gopal Gupta

CoRR, 2024

Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programs.

Matthew L. Daggitt, Wen Kokke, Robert Atkey, Natalia Slusarz, Luca Arnaboldi, Ekaterina Komendantskaya

CoRR, 2024

Taming Differentiable Logics with Coq Formalisation.

Reynald Affeldt, Alessandro Bruni, Ekaterina Komendantskaya, Natalia Slusarz, Kathrin Stark

Proceedings of the 15th International Conference on Interactive Theorem Proving, 2024

A Neurosymbolic Framework for Bias Correction in Convolutional Neural Networks.

Parth Padalkar, Natalia Slusarz, Ekaterina Komendantskaya, Gopal Gupta

Proceedings of the Workshop Proceedings of the 40th International Conference on Logic Programming (ICLP-WS 2024) co-located with the 40th International Conference on Logic Programming (ICLP 2024), 2024

2023

Logic of Differentiable Logics: Towards a Uniform Semantics of DL.

Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart, Kathrin Stark

Proceedings of the LPAR 2023: Proceedings of 24th International Conference on Logic for Programming, 2023

The Vehicle Tutorial: Neural Network Verification with Vehicle.

Matthew L. Daggitt, Wen Kokke, Ekaterina Komendantskaya, Robert Atkey, Luca Arnaboldi, Natalia Slusarz, Marco Casadio, Ben Coke, Jeonghyeon Lee

Proceedings of the 6th Workshop on Formal Methods for ML-Enabled Autonomous Systems, 2023

2022

Differentiable Logics for Neural Network Training and Verification.

Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart

Proceedings of the Software Verification and Formal Methods for ML-Enabled Autonomous Systems, 2022