Prati
John D Co-Reyes
John D Co-Reyes
Research Scientist at Google DeepMind
Potvrđena adresa e-pošte na google.com - Početna stranica
Naslov
Citirano
Citirano
Godina
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ...
arXiv preprint arXiv:2312.11805, 2023
35612023
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ...
arXiv preprint arXiv:2403.05530, 2024
14022024
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
2282020
Ex2: Exploration with exemplar models for deep reinforcement learning
J Fu, JD Co-Reyes, S Levine
NeurIPS, spotlight, 2017
1922017
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
1902018
Beyond human data: Scaling self-training for problem-solving with language models
A Singh, JD Co-Reyes, R Agarwal, A Anand, P Patil, X Garcia, PJ Liu, ...
arXiv preprint arXiv:2312.06585, 2023
1082023
Many-shot in-context learning
R Agarwal, A Singh, L Zhang, B Bohnet, L Rosias, S Chan, B Zhang, ...
Advances in Neural Information Processing Systems 37, 76930-76966, 2024
1062024
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, ...
Advances in Neural Information Processing Systems 36, 7730-7742, 2023
1062023
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
962021
Training language models to self-correct via reinforcement learning
A Kumar, V Zhuang, R Agarwal, Y Su, JD Co-Reyes, A Singh, K Baumli, ...
arXiv preprint arXiv:2409.12917, 2024
832024
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
752023
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
732018
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
402023
Ecological reinforcement learning
JD Co-Reyes, S Sanjeev, G Berseth, A Gupta, S Levine
arXiv preprint arXiv:2006.12478, 2020
342020
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
232019
Training language models to self-correct via reinforcement learning, 2024
A Kumar, V Zhuang, R Agarwal, Y Su, JD Co-Reyes, A Singh, K Baumli, ...
URL https://arxiv. org/abs/2409.12917, 0
15
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
112021
Small-scale proxies for large-scale transformer training instabilities, 2023
M Wortsman, PJ Liu, L Xiao, K Everett, A Alemi, B Adlam, JD Co-Reyes, ...
URL https://arxiv. org/abs/2309.14322, 0
8*
RL-DARTS: differentiable architecture search for reinforcement learning
Y Miao, X Song, D Peng, S Yue, JD Co-Reyes, E Brevdo, A Faust
72021
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
62021
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