| 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 | 99 | 2024 |
| An SMT-based approach for verifying binarized neural networks G Amir, H Wu, C Barrett, G Katz International Conference on Tools and Algorithms for the Construction and …, 2021 | 98 | 2021 |
| 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 | 76 | 2022 |
| Towards scalable verification of deep reinforcement learning G Amir, M Schapira, G Katz 2021 formal methods in computer aided design (FMCAD), 193-203, 2021 | 72 | 2021 |
| 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 | 61 | 2023 |
| Micro and macroevolution of sea anemone venom phenotype EG Smith, JM Surm, J Macrander, A Simhi, G Amir, MY Sachkova, ... Nature Communications 14 (1), 249, 2023 | 36* | 2023 |
| Local vs. Global Interpretability: A Computational Complexity Perspective S Bassan, G Amir, G Katz International Conference on Machine Learning (ICML), 2024 | 28 | 2024 |
| Formally explaining neural networks within reactive systems S Bassan, G Amir, D Corsi, I Refaeli, G Katz 2023 Formal Methods in Computer-Aided Design (FMCAD), 1-13, 2023 | 26* | 2023 |
| Enforcing Specific Behaviours via Constrained DRL and Scenario-Based Programming D Corsi, R Yerushalmi, G Amir, A Farinelli, D Harel, G Katz International Conference on Neural Information Processing, 284-302, 2024 | 25* | 2024 |
| Verifying generalization in deep learning G Amir, O Maayan, T Zelazny, G Katz, M Schapira International Conference on Computer Aided Verification, 438-455, 2023 | 23 | 2023 |
| Verification-Aided Deep Ensemble Selection G Amir, T Zelazny, G Katz, M Schapira Formal Methods in Computer-Aided Design (FMCAD), 27-37, 2022 | 22 | 2022 |
| Formally Verifying Deep Reinforcement Learning Controllers with Lyapunov Barrier Certificates 2024 Formal Methods in Computer Aided Design (FMCAD), 95-106, 2024 | 17* | 2024 |
| Shield synthesis for LTL modulo theories A Rodriguez, G Amir, D Corsi, C Sánchez, G Katz Proceedings of the AAAI Conference on Artificial Intelligence 39 (14), 15134 …, 2025 | 15 | 2025 |
| Verification-Guided Shielding for Deep Reinforcement Learning D Corsi, G Amir, A Rodríguez, C Sánchez, G Katz, R Fox The 1st Reinforcement Learning Conference (RLC), 2024 | 15 | 2024 |
| veriFIRE: verifying an industrial, learning-based wildfire detection system G Amir, Z Freund, G Katz, E Mandelbaum, I Refaeli International Symposium on Formal Methods, 648-656, 2023 | 15 | 2023 |
| Scenario-Assisted Deep Reinforcement Learning AM Raz Yerushalmi, Guy Amir, Achiya Elyasaf, David Harel, Guy Katz MODELSWARD 2022: the 10th International Conference on Model-Driven …, 2022 | 15* | 2022 |
| Hard to Explain: On the Computational Hardness of In-Distribution Model Interpretation G Amir, S Bassan, G Katz European Conference on Artificial Intelligence (ECAI), 2024 | 12 | 2024 |
| 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 | 10 | 2023 |
| Analyzing adversarial inputs in deep reinforcement learning D Corsi, G Amir, G Katz, A Farinelli arXiv preprint arXiv:2402.05284, 2024 | 9 | 2024 |
| Safe and Reliable Training of Learning-Based Aerospace Controllers U Mandal, G Amir, H Wu, I Daukantas, FL Newell, U Ravaioli, B Meng, ... 2024 AIAA DATC/IEEE 43rd Digital Avionics Systems Conference (DASC), 1-10, 2024 | 8 | 2024 |
Guy KatzThe Hebrew University of JerusalemVerified email at cs.huji.ac.il
