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John D Co-Reyes
John D Co-Reyes
Research Scientist at Google Brain
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
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
1762020
Ex2: Exploration with exemplar models for deep reinforcement learning
J Fu, JD Co-Reyes, S Levine
NeurIPS, spotlight, 2017
1692017
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
1572018
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
672021
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
612018
Ecological reinforcement learning
JD Co-Reyes, S Sanjeev, G Berseth, A Gupta, S Levine
arXiv preprint arXiv:2006.12478, 2020
262020
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
202019
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
62021
RL-DARTS: differentiable architecture search for reinforcement learning
Y Miao, X Song, D Peng, S Yue, JD Co-Reyes, E Brevdo, A Faust
62021
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
52021
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
32022
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
32022
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
22021
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
12023
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
12023
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
12022
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
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