Artykuły udostępnione publicznie: - Guy KatzWięcej informacji
Niedostępny w żadnym miejscu: 1
Enhancing deep reinforcement learning with scenario-based modeling
R Yerushalmi, G Amir, A Elyasaf, D Harel, G Katz, A Marron
SN computer science 4 (2), 156, 2023
Upoważnienia: National Natural Science Foundation of China, Federal Ministry of Education …
Dostępne w jakimś miejscu: 26
The marabou framework for verification and analysis of deep neural networks
G Katz, DA Huang, D Ibeling, K Julian, C Lazarus, R Lim, P Shah, ...
Computer Aided Verification: 31st International Conference, CAV 2019, New …, 2019
Upoważnienia: US National Science Foundation, US Department of Defense
Deepsafe: A data-driven approach for assessing robustness of neural networks
D Gopinath, G Katz, CS Păsăreanu, C Barrett
Automated Technology for Verification and Analysis: 16th International …, 2018
Upoważnienia: US National Science Foundation, US National Aeronautics and Space Administration
SMTCoq: A plug-in for integrating SMT solvers into Coq
B Ekici, A Mebsout, C Tinelli, C Keller, G Katz, A Reynolds, C Barrett
Computer Aided Verification: 29th International Conference, CAV 2017 …, 2017
Upoważnienia: US Department of Defense
An SMT-based approach for verifying binarized neural networks
G Amir, H Wu, C Barrett, G Katz
Tools and Algorithms for the Construction and Analysis of Systems: 27th …, 2021
Upoważnienia: US National Science Foundation
Verifying deep-RL-driven systems
Y Kazak, C Barrett, G Katz, M Schapira
Proceedings of the 2019 workshop on network meets AI & ML, 83-89, 2019
Upoważnienia: US National Science Foundation, European Commission
Verifying learning-augmented systems
T Eliyahu, Y Kazak, G Katz, M Schapira
Proceedings of the 2021 ACM SIGCOMM 2021 Conference, 305-318, 2021
Upoważnienia: US National Science Foundation
Verifying recurrent neural networks using invariant inference
Y Jacoby, C Barrett, G Katz
Automated Technology for Verification and Analysis: 18th International …, 2020
Upoważnienia: US National Science Foundation
Neural network robustness as a verification property: a principled case study
M Casadio, E Komendantskaya, ML Daggitt, W Kokke, G Katz, G Amir, ...
International conference on computer aided verification, 219-231, 2022
Upoważnienia: UK Engineering and Physical Sciences Research Council
Towards scalable verification of deep reinforcement learning
G Amir, M Schapira, G Katz
2021 formal methods in computer aided design (FMCAD), 193-203, 2021
Upoważnienia: US National Science Foundation
ScenarioTools–A tool suite for the scenario-based modeling and analysis of reactive systems
J Greenyer, D Gritzner, T Gutjahr, F König, N Glade, A Marron, G Katz
Science of Computer Programming 149, 15-27, 2017
Upoważnienia: Federal Ministry of Education and Research, Germany
Simplifying neural networks using formal verification
S Gokulanathan, A Feldsher, A Malca, C Barrett, G Katz
NASA Formal Methods: 12th International Symposium, NFM 2020, Moffett Field …, 2020
Upoważnienia: US National Science Foundation
Efficient neural network analysis with sum-of-infeasibilities
H Wu, A Zeljić, G Katz, C Barrett
International Conference on Tools and Algorithms for the Construction and …, 2022
Upoważnienia: US National Science Foundation, US Department of Defense
Global optimization of objective functions represented by ReLU networks
CA Strong, H Wu, A Zeljić, KD Julian, G Katz, C Barrett, MJ Kochenderfer
Machine Learning 112 (10), 3685-3712, 2023
Upoważnienia: US Department of Defense
An abstraction-refinement approach to verifying convolutional neural networks
M Ostrovsky, C Barrett, G Katz
International Symposium on Automated Technology for Verification and …, 2022
Upoważnienia: US National Science Foundation
Verifying learning-based robotic navigation systems
G Amir, D Corsi, R Yerushalmi, L Marzari, D Harel, A Farinelli, G Katz
International Conference on Tools and Algorithms for the Construction and …, 2023
Upoważnienia: National Natural Science Foundation of China, Federal Ministry of Education …
Scenario-Based Modeling and Synthesis for Reactive Systems with Dynamic System Structure in ScenarioTools.
J Greenyer, D Gritzner, G Katz, A Marron
D&P@ MoDELS, 16-23, 2016
Upoważnienia: Federal Ministry of Education and Research, Germany
Marabou 2.0: a versatile formal analyzer of neural networks
H Wu, O Isac, A Zeljić, T Tagomori, M Daggitt, W Kokke, I Refaeli, G Amir, ...
International Conference on Computer Aided Verification, 249-264, 2024
Upoważnienia: UK Engineering and Physical Sciences Research Council, European Commission
Scaling-up behavioral programming: steps from basic principles to application architectures
D Harel, G Katz
Proceedings of the 4th International Workshop on Programming based on Actors …, 2014
Upoważnienia: European Commission
Non-intrusive repair of safety and liveness violations in reactive programs
D Harel, G Katz, A Marron, G Weiss
Transactions on Computational Collective Intelligence XVI, 1-33, 2014
Upoważnienia: European Commission
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