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 | 2590 | 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 | 1110 | 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 | 1048 | 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 | 882 | 2020 |
Awac: Accelerating online reinforcement learning with offline datasets A Nair, A Gupta, M Dalal, S Levine arXiv preprint arXiv:2006.09359, 2020 | 496 | 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 | 427 | 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 | 414 | 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 | 393 | 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 | 347 | 2019 |
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 | 329 | 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 | 210 | 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 | 206 | 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 | 178* | 2019 |
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 | 174 | 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 | 172 | 2018 |
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 | 170 | 2015 |
Unsupervised meta-learning for reinforcement learning A Gupta, B Eysenbach, C Finn, S Levine arXiv preprint arXiv:1806.04640, 2018 | 135 | 2018 |
Learning actionable representations with goal-conditioned policies D Ghosh, A Gupta, S Levine arXiv preprint arXiv:1811.07819, 2018 | 132 | 2018 |
Open x-embodiment: Robotic learning datasets and rt-x models A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ... arXiv preprint arXiv:2310.08864, 2023 | 127 | 2023 |
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 | 125 | 2020 |