| Deep reinforcement learning in large discrete action spaces G Dulac-Arnold, R Evans, H van Hasselt, P Sunehag, T Lillicrap, J Hunt, ... arXiv preprint arXiv:1512.07679, 2015 | 363 | 2015 |
| A Dual Approach to Scalable Verification of Deep Networks. K Dvijotham, R Stanforth, S Gowal, TA Mann, P Kohli UAI 1 (2), 3, 2018 | 296 | 2018 |
| On the effectiveness of interval bound propagation for training verifiably robust models S Gowal, K Dvijotham, R Stanforth, R Bunel, C Qin, J Uesato, ... arXiv preprint arXiv:1810.12715, 2018 | 258 | 2018 |
| Uncovering the limits of adversarial training against norm-bounded adversarial examples S Gowal, C Qin, J Uesato, T Mann, P Kohli arXiv preprint arXiv:2010.03593, 2020 | 97 | 2020 |
| Scalable verified training for provably robust image classification S Gowal, KD Dvijotham, R Stanforth, R Bunel, C Qin, J Uesato, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 70 | 2019 |
| Adaptive skills adaptive partitions (ASAP) DJ Mankowitz, TA Mann, S Mannor Advances in neural information processing systems 29, 2016 | 53 | 2016 |
| Robust reinforcement learning for continuous control with model misspecification DJ Mankowitz, N Levine, R Jeong, Y Shi, J Kay, A Abdolmaleki, ... arXiv preprint arXiv:1906.07516, 2019 | 52 | 2019 |
| Scaling up approximate value iteration with options: Better policies with fewer iterations T Mann, S Mannor International conference on machine learning, 127-135, 2014 | 51 | 2014 |
| Approximate Value Iteration with Temporally Extended Actions SMDP Timothy A. Mann Journal of Artificial Intelligence Research 53, 375-438, 2015 | 49 | 2015 |
| Fixing data augmentation to improve adversarial robustness SA Rebuffi, S Gowal, DA Calian, F Stimberg, O Wiles, T Mann arXiv preprint arXiv:2103.01946, 2021 | 45 | 2021 |
| An alternative surrogate loss for pgd-based adversarial testing S Gowal, J Uesato, C Qin, PS Huang, T Mann, P Kohli arXiv preprint arXiv:1910.09338, 2019 | 45 | 2019 |
| How hard is my MDP?" The distribution-norm to the rescue" OA Maillard, TA Mann, S Mannor Advances in Neural Information Processing Systems 27, 2014 | 45 | 2014 |
| Time regularized interrupting options DJ Mankowitz, TA Mann, S Mannor Internation Conference on Machine Learning, 2014 | 37* | 2014 |
| Learning robust options D Mankowitz, T Mann, PL Bacon, D Precup, S Mannor Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 36 | 2018 |
| Achieving robustness in the wild via adversarial mixing with disentangled representations S Gowal, C Qin, PS Huang, T Cemgil, K Dvijotham, T Mann, P Kohli Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 34 | 2020 |
| Beyond greedy ranking: Slate optimization via list-CVAE R Jiang, S Gowal, TA Mann, DJ Rezende arXiv preprint arXiv:1803.01682, 2018 | 28 | 2018 |
| Off-policy model-based learning under unknown factored dynamics A Hallak, F Schnitzler, T Mann, S Mannor International Conference on Machine Learning, 711-719, 2015 | 28 | 2015 |
| Soft-robust actor-critic policy-gradient E Derman, DJ Mankowitz, TA Mann, S Mannor arXiv preprint arXiv:1803.04848, 2018 | 26 | 2018 |
| Directed exploration in reinforcement learning with transferred knowledge TA Mann, Y Choe European Workshop on Reinforcement Learning, 59-76, 2013 | 22 | 2013 |
| A bayesian approach to robust reinforcement learning E Derman, D Mankowitz, T Mann, S Mannor Uncertainty in Artificial Intelligence, 648-658, 2020 | 21 | 2020 |
Shie MannorProfessor of Electrical Engineering @ Technion & Researcher @ Nvidia ResearchVerifierad e-postadress på technion.ac.il
