| Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours L Pinto, A Gupta 2016 IEEE international conference on robotics and automation (ICRA), 3406-3413, 2016 | 1423 | 2016 |
| Robust adversarial reinforcement learning L Pinto, J Davidson, R Sukthankar, A Gupta Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017 | 1133 | 2017 |
| Reinforcement learning with augmented data M Laskin, K Lee, A Stooke, L Pinto, P Abbeel, A Srinivas Advances in neural information processing systems 33, 19884-19895, 2020 | 816 | 2020 |
| Open x-embodiment: Robotic learning datasets and rt-x models JJ Lim IEEE International Conference on Robotics and Automation, 2024 | 611* | 2024 |
| Asymmetric actor critic for image-based robot learning L Pinto, M Andrychowicz, P Welinder, W Zaremba, P Abbeel Robotics: Science and Systems, 2018, 2017 | 439 | 2017 |
| Learning to fly by crashing D Gandhi, L Pinto, A Gupta 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 421 | 2017 |
| Mastering visual continuous control: Improved data-augmented reinforcement learning D Yarats, R Fergus, A Lazaric, L Pinto arXiv preprint arXiv:2107.09645, 2021 | 377 | 2021 |
| Reinforcement learning with prototypical representations D Yarats, R Fergus, A Lazaric, L Pinto International Conference on Machine Learning, 11920-11931, 2021 | 261 | 2021 |
| Learning to manipulate deformable objects without demonstrations Y Wu, W Yan, T Kurutach, L Pinto, P Abbeel Robotics: Science and Systems, 2020, 2019 | 237 | 2019 |
| The curious robot: Learning visual representations via physical interactions L Pinto, D Gandhi, Y Han, YL Park, A Gupta Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 222 | 2016 |
| Behavior Transformers: Cloning modes with one stone NM Mahi Shafiullah, ZJ Cui, A Altanzaya, L Pinto arXiv e-prints, arXiv: 2206.11251, 2022 | 220* | 2022 |
| Learning predictive representations for deformable objects using contrastive estimation W Yan, A Vangipuram, P Abbeel, L Pinto Conference on Robot Learning, 564-574, 2021 | 218 | 2021 |
| Self-supervised policy adaptation during deployment N Hansen, R Jangir, Y Sun, G Alenyà, P Abbeel, AA Efros, L Pinto, ... arXiv preprint arXiv:2007.04309, 2020 | 185 | 2020 |
| Urlb: Unsupervised reinforcement learning benchmark M Laskin, D Yarats, H Liu, K Lee, A Zhan, K Lu, C Cang, L Pinto, P Abbeel arXiv preprint arXiv:2110.15191, 2021 | 179 | 2021 |
| Learning to push by grasping: Using multiple tasks for effective learning L Pinto, A Gupta 2017 IEEE international conference on robotics and automation (ICRA), 2161-2168, 2017 | 179 | 2017 |
| Robot learning in homes: Improving generalization and reducing dataset bias A Gupta, A Murali, DP Gandhi, L Pinto Advances in neural information processing systems 31, 2018 | 161 | 2018 |
| The surprising effectiveness of representation learning for visual imitation J Pari, NM Shafiullah, SP Arunachalam, L Pinto arXiv preprint arXiv:2112.01511, 2021 | 153 | 2021 |
| Clip-fields: Weakly supervised semantic fields for robotic memory NMM Shafiullah, C Paxton, L Pinto, S Chintala, A Szlam arXiv preprint arXiv:2210.05663, 2022 | 151* | 2022 |
| State-only imitation learning for dexterous manipulation I Radosavovic, X Wang, L Pinto, J Malik 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 133 | 2021 |
| Automatic curriculum learning through value disagreement Y Zhang, P Abbeel, L Pinto Advances in Neural Information Processing Systems 33, 7648-7659, 2020 | 130 | 2020 |
Abhinav GuptaProfessor, Robotics Institute, Carnegie Mellon UniversityVerified email at cs.cmu.edu
