| Actor-mimic: Deep multitask and transfer reinforcement learning E Parisotto, JL Ba, R Salakhutdinov arXiv preprint arXiv:1511.06342, 2015 | 580 | 2015 |
| Generating images from captions with attention E Mansimov, E Parisotto, JL Ba, R Salakhutdinov arXiv preprint arXiv:1511.02793, 2015 | 399 | 2015 |
| Neuro-symbolic program synthesis E Parisotto, A Mohamed, R Singh, L Li, D Zhou, P Kohli arXiv preprint arXiv:1611.01855, 2016 | 342 | 2016 |
| A generalist agent S Reed, K Zolna, E Parisotto, SG Colmenarejo, A Novikov, G Barth-Maron, ... arXiv preprint arXiv:2205.06175, 2022 | 283 | 2022 |
| The hanabi challenge: A new frontier for ai research N Bard, JN Foerster, S Chandar, N Burch, M Lanctot, HF Song, E Parisotto, ... Artificial Intelligence 280, 103216, 2020 | 274 | 2020 |
| Neural map: Structured memory for deep reinforcement learning E Parisotto, R Salakhutdinov arXiv preprint arXiv:1702.08360, 2017 | 262 | 2017 |
| Stabilizing transformers for reinforcement learning E Parisotto, F Song, J Rae, R Pascanu, C Gulcehre, S Jayakumar, ... International Conference on Machine Learning, 7487-7498, 2020 | 239 | 2020 |
| Efficient Exploration via State Marginal Matching L Lee, B Eysenbach, E Parisotto, E Xing, S Levine, R Salakhutdinov arXiv preprint arXiv:1906.05274, 2019 | 179 | 2019 |
| Active Neural Localization DS Chaplot, E Parisotto, R Salakhutdinov arXiv preprint arXiv:1801.08214, 2018 | 97 | 2018 |
| Gated path planning networks L Lee, E Parisotto, DS Chaplot, E Xing, R Salakhutdinov International Conference on Machine Learning, 2947-2955, 2018 | 83 | 2018 |
| Global pose estimation with an attention-based recurrent network E Parisotto, D Singh Chaplot, J Zhang, R Salakhutdinov Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 82 | 2018 |
| Shaking the foundations: delusions in sequence models for interaction and control PA Ortega, M Kunesch, G Delétang, T Genewein, J Grau-Moya, J Veness, ... arXiv preprint arXiv:2110.10819, 2021 | 22 | 2021 |
| Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation E Parisotto, R Salakhutdinov arXiv preprint arXiv:2104.01655, 2021 | 21 | 2021 |
| Concurrent Meta Reinforcement Learning E Parisotto, S Ghosh, SB Yalamanchi, V Chinnaobireddy, Y Wu, ... arXiv preprint arXiv:1903.02710, 2019 | 19 | 2019 |
| Neural network for program synthesis ASA Mohamed, R Singh, L Li, D Zhou, P Kohli, E Parisotto US Patent 10,795,645, 2020 | 17 | 2020 |
| In-context reinforcement learning with algorithm distillation M Laskin, L Wang, J Oh, E Parisotto, S Spencer, R Steigerwald, ... arXiv preprint arXiv:2210.14215, 2022 | 15 | 2022 |
| On proximal policy optimization’s heavy-tailed gradients S Garg, J Zhanson, E Parisotto, A Prasad, Z Kolter, Z Lipton, ... International Conference on Machine Learning, 3610-3619, 2021 | 8 | 2021 |
| Imitate and Repurpose: Learning Reusable Robot Movement Skills From Human and Animal Behaviors S Bohez, S Tunyasuvunakool, P Brakel, F Sadeghi, L Hasenclever, ... arXiv preprint arXiv:2203.17138, 2022 | 6 | 2022 |
| Structured State Space Models for In-Context Reinforcement Learning C Lu, Y Schroecker, A Gu, E Parisotto, J Foerster, S Singh, F Behbahani arXiv preprint arXiv:2303.03982, 2023 | 1 | 2023 |
| Neural map R Salakhutdinov, E Parisotto US Patent 11,521,058, 2022 | 1 | 2022 |
