| 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 | 280 | 2019 |
| Fast and Effective Robustness Certification. G Singh, T Gehr, M Mirman, M Püschel, MT Vechev NeurIPS 1 (4), 6, 2018 | 264 | 2018 |
| Boosting robustness certification of neural networks G Singh, T Gehr, M Püschel, M Vechev International Conference on Learning Representations, 2018 | 110* | 2018 |
| Fast polyhedra abstract domain G Singh, M Püschel, M Vechev Proceedings of the 44th ACM SIGPLAN Symposium on Principles of Programming …, 2017 | 80 | 2017 |
| 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 | 68 | 2019 |
| Certifying geometric robustness of neural networks M Balunović, M Baader, G Singh, T Gehr, M Vechev Advances in Neural Information Processing Systems 32, 2019 | 64 | 2019 |
| Making Numerical Program Analysis Fast G Singh, M Püschel, M Vechev Programming Language Design and Implementation (PLDI) 50 (6), 303-313, 2015 | 44 | 2015 |
| Fast Numerical Program Analysis with Reinforcement Learning G Singh, M Püschel, M Vechev International Conference on Computer Aided Verification, 211-229, 2018 | 30 | 2018 |
| 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 | 27 | 2017 |
| A Provable Defense for Deep Residual Networks M Mirman, G Singh, M Vechev arXiv preprint arXiv:1903.12519, 2019 | 16 | 2019 |
| Scaling Polyhedral Neural Network Verification on GPUs C Müller, F Serre, G Singh, M Püschel, M Vechev Proceedings of Machine Learning and Systems 3, 2021 | 15 | 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 | 15 | 2020 |
| 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 | 8* | 2021 |
| Adversarial Attacks on Probabilistic Autoregressive Forecasting Models R Dang-Nhu, G Singh, P Bielik, M Vechev International Conference on Machine Learning, 2020 | 7 | 2020 |
| PRIMA: general and precise neural network certification via scalable convex hull approximations MN Müller, G Makarchuk, G Singh, M Püschel, M Vechev Proceedings of the ACM on Programming Languages 6 (POPL), 1-33, 2022 | 6* | 2022 |
| Robustness Certification for Point Cloud Models T Lorenz, A Ruoss, M Balunović, G Singh, M Vechev arXiv preprint arXiv:2103.16652, 2021 | 3 | 2021 |
| 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 | | 2022 |
| 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 | | 2021 |
| Shared Certificates for Neural Network Verification C Sprecher, M Fischer, DI Dimitrov, G Singh, M Vechev arXiv preprint arXiv:2109.00542, 2021 | | 2021 |
| Scalable Inference of Symbolic Adversarial Examples DI Dimitrov, G Singh, T Gehr, M Vechev arXiv preprint arXiv:2007.12133, 2020 | | 2020 |
Martin VechevProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
