| Image augmentation is all you need: Regularizing deep reinforcement learning from pixels I Kostrikov*, D Yarats*, R Fergus arXiv preprint arXiv:2004.13649, 2020 | 786* | 2020 |
| Offline reinforcement learning with implicit q-learning I Kostrikov, A Nair, S Levine arXiv preprint arXiv:2110.06169, 2021 | 721 | 2021 |
| Planet-photo geolocation with convolutional neural networks T Weyand, I Kostrikov, J Philbin Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 528 | 2016 |
| Improving sample efficiency in model-free reinforcement learning from images D Yarats, A Zhang, I Kostrikov, B Amos, J Pineau, R Fergus Proceedings of the aaai conference on artificial intelligence 35 (12), 10674 …, 2021 | 435 | 2021 |
| Intrinsic motivation and automatic curricula via asymmetric self-play S Sukhbaatar, Z Lin, I Kostrikov, G Synnaeve, A Szlam, R Fergus arXiv preprint arXiv:1703.05407, 2017 | 433 | 2017 |
| Discriminator-actor-critic: Addressing sample inefficiency and reward bias in adversarial imitation learning I Kostrikov, KK Agrawal, D Dwibedi, S Levine, J Tompson arXiv preprint arXiv:1809.02925, 2018 | 329 | 2018 |
| Offline Reinforcement Learning with Fisher Divergence Critic Regularization I Kostrikov, J Tompson, R Fergus, O Nachum arXiv preprint arXiv:2103.08050, 2021 | 301 | 2021 |
| Algaedice: Policy gradient from arbitrary experience O Nachum, B Dai, I Kostrikov, Y Chow, L Li, D Schuurmans arXiv preprint arXiv:1912.02074, 2019 | 248 | 2019 |
| Pytorch implementations of reinforcement learning algorithms I Kostrikov GitHub repository: https://github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail, 2018 | 230 | 2018 |
| Automatic data augmentation for generalization in deep reinforcement learning R Raileanu, M Goldstein, D Yarats, I Kostrikov, R Fergus arXiv preprint arXiv:2006.12862, 2020 | 210* | 2020 |
| Imitation learning via off-policy distribution matching I Kostrikov, O Nachum, J Tompson arXiv preprint arXiv:1912.05032, 2019 | 202 | 2019 |
| Rvs: What is essential for offline rl via supervised learning? S Emmons, B Eysenbach, I Kostrikov, S Levine arXiv preprint arXiv:2112.10751, 2021 | 190 | 2021 |
| An Efficient Convolutional Network for Human Pose Estimation. U Rafi, B Leibe, J Gall, I Kostrikov BMVC 1, 2, 2016 | 172 | 2016 |
| Training diffusion models with reinforcement learning K Black, M Janner, Y Du, I Kostrikov, S Levine arXiv preprint arXiv:2305.13301, 2023 | 167* | 2023 |
| A walk in the park: Learning to walk in 20 minutes with model-free reinforcement learning L Smith*, I Kostrikov*, S Levine arXiv preprint arXiv:2208.07860, 2022 | 105* | 2022 |
| Depth Sweep Regression Forests for Estimating 3D Human Pose from Images. I Kostrikov, J Gall BMVC 1 (2), 5, 2014 | 102 | 2014 |
| Efficient Online Reinforcement Learning with Offline Data PJ Ball*, L Smith*, I Kostrikov*, S Levine arXiv preprint arXiv:2302.02948, 2023 | 101 | 2023 |
| Surface networks I Kostrikov, Z Jiang, D Panozzo, D Zorin, J Bruna Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 97 | 2018 |
| Idql: Implicit q-learning as an actor-critic method with diffusion policies P Hansen-Estruch, I Kostrikov, M Janner, JG Kuba, S Levine arXiv preprint arXiv:2304.10573, 2023 | 86 | 2023 |
| Offline rl for natural language generation with implicit language q learning C Snell, I Kostrikov, Y Su, M Yang, S Levine arXiv preprint arXiv:2206.11871, 2022 | 80 | 2022 |
Sergey LevineUC Berkeley, Physical Intelligence在 eecs.berkeley.edu 的电子邮件经过验证
