| Reluplex: An efficient SMT solver for verifying deep neural networks G Katz, C Barrett, DL Dill, K Julian, MJ Kochenderfer International Conference on Computer Aided Verification, 97-117, 2017 | 780 | 2017 |
| Deepsafe: A data-driven approach for assessing robustness of neural networks D Gopinath, G Katz, CS Păsăreanu, C Barrett International Symposium on Automated Technology for Verification and …, 2018 | 96* | 2018 |
| 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, ... International Conference on Computer Aided Verification, 443-452, 2019 | 86 | 2019 |
| Towards proving the adversarial robustness of deep neural networks G Katz, C Barrett, DL Dill, K Julian, MJ Kochenderfer arXiv preprint arXiv:1709.02802, 2017 | 84 | 2017 |
| Ground-Truth Adversarial Examples N Carlini, G Katz, C Barrett, DL Dill arXiv preprint arXiv:1709.10207v1, 2017 | 52 | 2017 |
| Provably minimally-distorted adversarial examples N Carlini, G Katz, C Barrett, DL Dill arXiv preprint arXiv:1709.10207, 2017 | 46 | 2017 |
| SMTCoq: A plug-in for integrating SMT solvers into Coq B Ekici, A Mebsout, C Tinelli, C Keller, G Katz, A Reynolds, C Barrett International Conference on Computer Aided Verification, 126-133, 2017 | 45 | 2017 |
| On composing and proving the correctness of reactive behavior D Harel, A Kantor, G Katz, A Marron, L Mizrahi, G Weiss 2013 Proceedings of the International Conference on Embedded Software …, 2013 | 28 | 2013 |
| 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 | 26 | 2017 |
| Non-intrusive repair of reactive programs D Harel, G Katz, A Marron, G Weiss 2012 IEEE 17th International Conference on Engineering of Complex Computer …, 2012 | 25 | 2012 |
| 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 | 22 | 2016 |
| 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 | 19 | 2014 |
| 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 | 18 | 2019 |
| On module-based abstraction and repair of behavioral programs G Katz International Conference on Logic for Programming Artificial Intelligence …, 2013 | 18 | 2013 |
| Toward scalable verification for safety-critical deep networks L Kuper, G Katz, J Gottschlich, K Julian, C Barrett, M Kochenderfer arXiv preprint arXiv:1801.05950, 2018 | 17 | 2018 |
| 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 | 17 | 2014 |
| Relaxing synchronization constraints in behavioral programs D Harel, A Kantor, G Katz International Conference on Logic for Programming Artificial Intelligence …, 2013 | 17 | 2013 |
| On the succinctness of idioms for concurrent programming D Harel, G Katz, R Lampert, A Marron, G Weiss 26th International Conference on Concurrency Theory (CONCUR 2015), 2015 | 16 | 2015 |
| An abstraction-based framework for neural network verification YY Elboher, J Gottschlich, G Katz International Conference on Computer Aided Verification, 43-65, 2020 | 14 | 2020 |
| Wise computing: toward endowing system development with proactive wisdom D Harel, G Katz, R Marelly, A Marron Computer 51 (2), 14-26, 2018 | 14* | 2018 |
