| 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 | 861 | 2019 |
| Fast and effective robustness certification G Singh, T Gehr, M Mirman, M Püschel, M Vechev Advances in neural information processing systems 31, 2018 | 641 | 2018 |
| Boosting robustness certification of neural networks G Singh, T Gehr, M Püschel, M Vechev International conference on learning representations, 2019 | 254 | 2019 |
| Beyond the single neuron convex barrier for neural network certification G Singh, R Ganvir, M Püschel, M Vechev Advances in Neural Information Processing Systems 32, 15098-15109, 2019 | 237 | 2019 |
| PRIMA: general and precise neural network certification via scalable convex hull approximations. MN Müller, G Makarchuk, G Singh, M Püschel, MT Vechev Proc. ACM Program. Lang. 6 (POPL), 1-33, 2022 | 151* | 2022 |
| Certifying geometric robustness of neural networks M Balunovic, M Baader, G Singh, T Gehr, M Vechev Advances in Neural Information Processing Systems 32, 2019 | 146 | 2019 |
| Fast polyhedra abstract domain G Singh, M Püschel, M Vechev Proceedings of the 44th ACM SIGPLAN Symposium on Principles of Programming …, 2017 | 142 | 2017 |
| Scaling polyhedral neural network verification on GPUs C Müller, F Serre, G Singh, M Püschel, M Vechev Proceedings of Machine Learning and Systems 3, 733-746, 2021 | 81* | 2021 |
| Making Numerical Program Analysis Fast G Singh, M Püschel, M Vechev Programming Language Design and Implementation (PLDI) 50 (6), 303-313, 2015 | 63 | 2015 |
| Scalable Polyhedral Verification of Recurrent Neural Networks W Ryou, J Chen, M Balunovic, G Singh, A Dan, M Vechev International Conference on Computer Aided Verification, 225-248, 2021 | 54* | 2021 |
| A practical construction for decomposing numerical abstract domains G Singh, M Püschel, M Vechev Proceedings of the ACM on Programming Languages 2 (POPL), 1-28, 2017 | 48 | 2017 |
| Improving llm code generation with grammar augmentation S Ugare, T Suresh, H Kang, S Misailovic, G Singh arXiv preprint arXiv:2403.01632, 2024 | 41* | 2024 |
| Fast numerical program analysis with reinforcement learning G Singh, M Püschel, M Vechev Computer Aided Verification: 30th International Conference, CAV 2018, Held …, 2018 | 39 | 2018 |
| FIRE: enabling reciprocity for FDD MIMO systems Z Liu, G Singh, C Xu, D Vasisht Proceedings of the 27th Annual International Conference on Mobile Computing …, 2021 | 35 | 2021 |
| Robustness certification for point cloud models T Lorenz, A Ruoss, M Balunović, G Singh, M Vechev Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 33 | 2021 |
| Learning fast and precise numerical analysis J He, G Singh, M Püschel, M Vechev Proceedings of the 41st ACM SIGPLAN Conference on Programming Language …, 2020 | 33 | 2020 |
| Adversarial Attacks on Probabilistic Autoregressive Forecasting Models R Dang-Nhu, G Singh, P Bielik, M Vechev International Conference on Machine Learning, 2020 | 30 | 2020 |
| A Provable Defense for Deep Residual Networks M Mirman, G Singh, M Vechev arXiv preprint arXiv:1903.12519, 2019 | 25 | 2019 |
| A dual number abstraction for static analysis of Clarke Jacobians J Laurel, R Yang, G Singh, S Misailovic Proceedings of the ACM on Programming Languages 6 (POPL), 1-30, 2022 | 21 | 2022 |
| Provable Defense Against Geometric Transformations R Yang, J Laurel, S Misailovic, G Singh International Conference on Learning Representations (ICLR 2023), 2023 | 19* | 2023 |
Martin VechevFull Professor of Computer Science, ETH Zurich; Scientific Director, INSAIT;確認したメール アドレス: inf.ethz.ch