| 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 | 958 | 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 | 568 | 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 | 520 | 2017 |
| 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 | 284 | 2017 |
| 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 | 248 | 2018 |
| 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 | 245 | 2018 |
| 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 | 220 | 2020 |
| 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 | 209 | 2017 |
| 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 | 137 | 2016 |
| 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 | 132 | 2015 |
| Awac: Accelerating online reinforcement learning with offline datasets A Nair, A Gupta, M Dalal, S Levine arXiv preprint arXiv:2006.09359, 2020 | 118 | 2020 |
| 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 | 108 | 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 | 104 | 2019 |
| 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 | 103 | 2019 |
| Unsupervised meta-learning for reinforcement learning A Gupta, B Eysenbach, C Finn, S Levine arXiv preprint arXiv:1806.04640, 2018 | 94 | 2018 |
| 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 | 87 | 2020 |
| Learning actionable representations with goal-conditioned policies D Ghosh, A Gupta, S Levine arXiv preprint arXiv:1811.07819, 2018 | 76 | 2018 |
| Learning dexterous manipulation policies from experience and imitation V Kumar, A Gupta, E Todorov, S Levine arXiv preprint arXiv:1611.05095, 2016 | 61 | 2016 |
| Automatically composing representation transformations as a means for generalization MB Chang, A Gupta, S Levine, TL Griffiths arXiv preprint arXiv:1807.04640, 2018 | 58 | 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 | 55 | 2020 |
Sergey LevineUC Berkeley, GoogleZweryfikowany adres z eecs.berkeley.edu
