John D Co-Reyes

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Sergey LevineUC Berkeley, GoogleVerified email at eecs.berkeley.edu
Abhishek GuptaUniversity of WashingtonVerified email at cs.washington.edu
Chelsea FinnStanford University, GoogleVerified email at cs.stanford.edu
Pieter AbbeelUC Berkeley | Covariant.AIVerified email at cs.berkeley.edu
Suvansh SanjeevCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Aleksandra FaustGoogle Brain, Mountain View, CAVerified email at google.com
Yingjie MiaoGoogleVerified email at buffalo.edu
Joshua B. TenenbaumMITVerified email at mit.edu
Jiajun WuStanford UniversityVerified email at cs.stanford.edu
Michael JannerUC BerkeleyVerified email at berkeley.edu
Rishi VeerapaneniCMUVerified email at andrew.cmu.edu
Daiyi PengGoogle Research, Brain TeamVerified email at google.com
Glen BersethAssitant Professor - Université de MontréalVerified email at umontreal.ca
Justin FuUC BerkeleyVerified email at berkeley.edu
Michael B. ChangUC Berkeley, Swiss AI Lab IDSIA, Massachusetts Institute of TechnologyVerified email at berkeley.edu
Benjamin EysenbachCMU, GoogleVerified email at google.com
Yu Xuan LiuUniversity of California BerkeleyVerified email at berkeley.edu
Esteban RealGoogle BrainVerified email at google.com
John DeNeroUC BerkeleyVerified email at berkeley.edu
Jacob AndreasMITVerified email at mit.edu

John D Co-Reyes

Research Scientist at Google Brain

Verified email at google.com - Homepage

artificial intelligence reinforcement learning machine learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Ex2: Exploration with exemplar models for deep reinforcement learning J Fu, JD Co-Reyes, S Levine NeurIPS, spotlight, 2017	143	2017
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	138	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	134	2018
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	50	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	44	2021
Ecological reinforcement learning JD Co-Reyes, S Sanjeev, G Berseth, A Gupta, S Levine arXiv preprint arXiv:2006.12478, 2020	22	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	18	2019
RL-DARTS: differentiable architecture search for reinforcement learning Y Miao, X Song, D Peng, S Yue, JD Co-Reyes, E Brevdo, A Faust	5	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	3	2021
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	2	2021
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
Multi-objective evolution for generalizable policy gradient algorithms JJ Garau-Luis, Y Miao, JD Co-Reyes, A Parisi, J Tan, E Real, A Faust arXiv preprint arXiv:2204.04292, 2022	1	2022
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		2022
Building Reinforcement Learning Algorithms that Generalize: From Latent Dynamics Models to Meta-Learning JD Co-Reyes		2021
Object Abstraction in Visual Model-Based Reinforcement Learning R Veerapaneni, JD Co-Reyes, M Chang, M Janner, C Finn, J Wu, ...
Guiding Policies with Language via Meta-Learning JDCRA Gupta, SSN Altieri, JDNPA SergeyLevine

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