| Ai2: Safety and robustness certification of neural networks with abstract interpretation T Gehr, M Mirman, D Drachsler-Cohen, P Tsankov, S Chaudhuri, ... 2018 IEEE Symposium on Security and Privacy (SP), 3-18, 2018 | 563 | 2018 |
| Differentiable abstract interpretation for provably robust neural networks M Mirman, T Gehr, M Vechev International Conference on Machine Learning, 3578-3586, 2018 | 343 | 2018 |
| An abstract domain for certifying neural networks G Singh, T Gehr, M Püschel, M Vechev Proceedings of the ACM on Programming Languages 3 (POPL), 1-30, 2019 | 330 | 2019 |
| Fast and effective robustness certification G Singh, T Gehr, M Mirman, M Püschel, M Vechev Advances in neural information processing systems 31, 2018 | 297 | 2018 |
| Boosting robustness certification of neural networks G Singh, T Gehr, M Püschel, M Vechev International conference on learning representations, 2018 | 126* | 2018 |
| PSI: Exact Symbolic Inference for Probabilistic Programs T Gehr, S Misailovic, M Vechev International Conference on Computer Aided Verification, 62-83, 2016 | 114 | 2016 |
| Dl2: Training and querying neural networks with logic M Fischer, M Balunovic, D Drachsler-Cohen, T Gehr, C Zhang, M Vechev International Conference on Machine Learning, 1931-1941, 2019 | 75 | 2019 |
| Certifying geometric robustness of neural networks M Balunovic, M Baader, G Singh, T Gehr, M Vechev Advances in Neural Information Processing Systems 32, 2019 | 69 | 2019 |
| Silq: A high-level quantum language with safe uncomputation and intuitive semantics B Bichsel, M Baader, T Gehr, M Vechev Proceedings of the 41st ACM SIGPLAN Conference on Programming Language …, 2020 | 57 | 2020 |
| Dp-finder: Finding differential privacy violations by sampling and optimization B Bichsel, T Gehr, D Drachsler-Cohen, P Tsankov, M Vechev Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications …, 2018 | 39 | 2018 |
| Learning commutativity specifications T Gehr, D Dimitrov, M Vechev International Conference on Computer Aided Verification, 307-323, 2015 | 35 | 2015 |
| Fine-grained semantics for probabilistic programs B Bichsel, T Gehr, M Vechev European Symposium on Programming, 145-185, 2018 | 24 | 2018 |
| Bayonet: probabilistic inference for networks T Gehr, S Misailovic, P Tsankov, L Vanbever, P Wiesmann, M Vechev ACM SIGPLAN Notices 53 (4), 586-602, 2018 | 19 | 2018 |
| Probabilistic verification of network configurations S Steffen, T Gehr, P Tsankov, L Vanbever, M Vechev Proceedings of the Annual conference of the ACM Special Interest Group on …, 2020 | 17 | 2020 |
| Synthesis of probabilistic privacy enforcement M Kučera, P Tsankov, T Gehr, M Guarnieri, M Vechev Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications …, 2017 | 17 | 2017 |
| Incremental inference for probabilistic programs M Cusumano-Towner, B Bichsel, T Gehr, M Vechev, VK Mansinghka Proceedings of the 39th ACM SIGPLAN Conference on Programming Language …, 2018 | 14 | 2018 |
| λPSI: exact inference for higher-order probabilistic programs T Gehr, S Steffen, M Vechev Proceedings of the 41st ACM SIGPLAN Conference on Programming Language …, 2020 | 12 | 2020 |
| Robustness certification with generative models M Mirman, A Hägele, P Bielik, T Gehr, M Vechev Proceedings of the 42nd ACM SIGPLAN International Conference on Programming …, 2021 | 8 | 2021 |
| Training Neural Machines with Partial Traces M Mirman, D Dimitrov, P Djordjevich, T Gehr, M Vechev | 2* | 2018 |
| Symbolic Methods for Machine Intelligence T Gehr ETH Zurich, 2022 | | 2022 |
