| Entity abstraction in visual model-based reinforcement learning R Veerapaneni, JD Co-Reyes, M Chang, M Janner, C Finn, J Wu, ... Conference on Robot Learning, 1439-1456, 2020 | 176 | 2020 |
| Ex2: Exploration with exemplar models for deep reinforcement learning J Fu, JD Co-Reyes, S Levine NeurIPS, spotlight, 2017 | 169 | 2017 |
| 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 | 157 | 2018 |
| Evolving reinforcement learning algorithms JD Co-Reyes, Y Miao, D Peng, E Real, S Levine, QV Le, H Lee, A Faust International Conference on Learning Representations, oral presentation, 2021 | 67 | 2021 |
| Guiding policies with language via meta-learning JD Co-Reyes, A Gupta, S Sanjeev, N Altieri, J Andreas, J DeNero, ... International Conference on Learning Representations, 2018 | 61 | 2018 |
| Ecological reinforcement learning JD Co-Reyes, S Sanjeev, G Berseth, A Gupta, S Levine arXiv preprint arXiv:2006.12478, 2020 | 26 | 2020 |
| Meta-learning language-guided policy learning JD Co-Reyes, A Gupta, S Sanjeev, N Altieri, J DeNero, P Abbeel, ... International Conference on Learning Representations 3, 2019 | 20 | 2019 |
| Information is power: Intrinsic control via information capture N Rhinehart, J Wang, G Berseth, J Co-Reyes, D Hafner, C Finn, S Levine Advances in Neural Information Processing Systems 34, 10745-10758, 2021 | 6 | 2021 |
| RL-DARTS: differentiable architecture search for reinforcement learning Y Miao, X Song, D Peng, S Yue, JD Co-Reyes, E Brevdo, A Faust | 6 | 2021 |
| Intrinsic control of variational beliefs in dynamic partially-observed visual environments N Rhinehart, J Wang, G Berseth, JD Co-Reyes, D Hafner, C Finn, ... ICML 2021 Workshop on Unsupervised Reinforcement Learning, 2021 | 5 | 2021 |
| Differentiable architecture search for reinforcement learning Y Miao, X Song, JD Co-Reyes, D Peng, S Yue, E Brevdo, A Faust International Conference on Automated Machine Learning, 20/1-17, 2022 | 3 | 2022 |
| Multi-objective evolution for generalizable policy gradient algorithms JJ Garau-Luis, Y Miao, JD Co-Reyes, A Parisi, J Tan, E Real, A Faust ICLR 2022 Workshop on Generalizable Policy Learning in Physical World, 2022 | 3 | 2022 |
| Accelerating online reinforcement learning via model-based meta-learning JD Co-Reyes, S Feng, G Berseth, J Qui, S Levine Learning to Learn-Workshop at ICLR 2021, 2021 | 2 | 2021 |
| Improving Large Language Model Fine-tuning for Solving Math Problems Y Liu, A Singh, CD Freeman, JD Co-Reyes, PJ Liu arXiv preprint arXiv:2310.10047, 2023 | 1 | 2023 |
| Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research C Gulino, J Fu, W Luo, G Tucker, E Bronstein, Y Lu, J Harb, X Pan, ... arXiv preprint arXiv:2310.08710, 2023 | 1 | 2023 |
| Evolving Pareto-Optimal Actor-Critic Algorithms for Generalizability and Stability JJ Garau-Luis, Y Miao, JD Co-Reyes, A Parisi, J Tan, E Real, A Faust arXiv preprint arXiv:2204.04292, 2022 | 1 | 2022 |
| Frontier Language Models are not Robust to Adversarial Arithmetic, or" What do I need to say so you agree 2+ 2= 5? CD Freeman, L Culp, A Parisi, ML Bileschi, GF Elsayed, A Rizkowsky, ... arXiv preprint arXiv:2311.07587, 2023 | | 2023 |
| Small-scale proxies for large-scale Transformer training instabilities M Wortsman, PJ Liu, L Xiao, K Everett, A Alemi, B Adlam, JD Co-Reyes, ... arXiv preprint arXiv:2309.14322, 2023 | | 2023 |
| Guided Evolution with Binary Predictors for ML Program Search JD Co-Reyes, Y Miao, G Tucker, A Faust, E Real ICML 2023 Workshop: Sampling and Optimization in Discrete Space, 2023 | | 2023 |
| Building Reinforcement Learning Algorithms that Generalize: From Latent Dynamics Models to Meta-Learning JD Co-Reyes | | 2021 |
Sergey LevineUC Berkeley, GoogleVerified email at eecs.berkeley.edu
