| Soft actor-critic algorithms and applications T Haarnoja, A Zhou, K Hartikainen, G Tucker, S Ha, J Tan, V Kumar, ... arXiv preprint arXiv:1812.05905, 2018 | 3159 | 2018 |
| Diversity is all you need: Learning skills without a reward function B Eysenbach, A Gupta, J Ibarz, S Levine arXiv preprint arXiv:1802.06070, 2018 | 1250 | 2018 |
| Learning complex dexterous manipulation with deep reinforcement learning and demonstrations A Rajeswaran, V Kumar, A Gupta, G Vezzani, J Schulman, E Todorov, ... arXiv preprint arXiv:1709.10087, 2017 | 1208 | 2017 |
| Gradient surgery for multi-task learning T Yu, S Kumar, A Gupta, S Levine, K Hausman, C Finn Advances in Neural Information Processing Systems 33, 5824-5836, 2020 | 1105 | 2020 |
| Awac: Accelerating online reinforcement learning with offline datasets A Nair, A Gupta, M Dalal, S Levine arXiv preprint arXiv:2006.09359, 2020 | 626 | 2020 |
| Learning modular neural network policies for multi-task and multi-robot transfer C Devin, A Gupta, T Darrell, P Abbeel, S Levine 2017 IEEE international conference on robotics and automation (ICRA), 2169-2176, 2017 | 466 | 2017 |
| Meta-reinforcement learning of structured exploration strategies A Gupta, R Mendonca, YX Liu, P Abbeel, S Levine Advances in neural information processing systems 31, 2018 | 449 | 2018 |
| Imitation from observation: Learning to imitate behaviors from raw video via context translation YX Liu, A Gupta, P Abbeel, S Levine 2018 IEEE international conference on robotics and automation (ICRA), 1118-1125, 2018 | 434 | 2018 |
| Relay policy learning: Solving long-horizon tasks via imitation and reinforcement learning A Gupta, V Kumar, C Lynch, S Levine, K Hausman arXiv preprint arXiv:1910.11956, 2019 | 424 | 2019 |
| Open x-embodiment: Robotic learning datasets and rt-x models A O'Neill, A Rehman, A Gupta, A Maddukuri, A Gupta, A Padalkar, A Lee, ... arXiv preprint arXiv:2310.08864, 2023 | 416* | 2023 |
| Learning invariant feature spaces to transfer skills with reinforcement learning A Gupta, C Devin, YX Liu, P Abbeel, S Levine arXiv preprint arXiv:1703.02949, 2017 | 357 | 2017 |
| Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost H Zhu, A Gupta, A Rajeswaran, S Levine, V Kumar International Conference on Robotics and Automation (ICRA) 2019, 2019 | 256 | 2019 |
| Learning dexterous manipulation for a soft robotic hand from human demonstrations A Gupta, C Eppner, S Levine, P Abbeel 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 222 | 2016 |
| Learning to reach goals via iterated supervised learning D Ghosh, A Gupta, A Reddy, J Fu, C Devin, B Eysenbach, S Levine arXiv preprint arXiv:1912.06088, 2019 | 211* | 2019 |
| Guiding pretraining in reinforcement learning with large language models Y Du, O Watkins, Z Wang, C Colas, T Darrell, P Abbeel, A Gupta, ... International Conference on Machine Learning, 8657-8677, 2023 | 206 | 2023 |
| The ingredients of real-world robotic reinforcement learning H Zhu, J Yu, A Gupta, D Shah, K Hartikainen, A Singh, V Kumar, S Levine arXiv preprint arXiv:2004.12570, 2020 | 204 | 2020 |
| Learning force-based manipulation of deformable objects from multiple demonstrations AX Lee, H Lu, A Gupta, S Levine, P Abbeel 2015 IEEE International Conference on Robotics and Automation (ICRA), 177-184, 2015 | 185 | 2015 |
| Self-consistent trajectory autoencoder: Hierarchical reinforcement learning with trajectory embeddings J Co-Reyes, YX Liu, A Gupta, B Eysenbach, P Abbeel, S Levine International conference on machine learning, 1009-1018, 2018 | 183 | 2018 |
| Robel: Robotics benchmarks for learning with low-cost robots M Ahn, H Zhu, K Hartikainen, H Ponte, A Gupta, S Levine, V Kumar Conference on robot learning, 1300-1313, 2020 | 144 | 2020 |
| Learning actionable representations with goal-conditioned policies D Ghosh, A Gupta, S Levine arXiv preprint arXiv:1811.07819, 2018 | 144 | 2018 |
Sergey LevineUC Berkeley, Physical Intelligence在 eecs.berkeley.edu 的电子邮件经过验证
