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Thomas Hubert
Thomas Hubert
Google Deepmind
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Cited by
Cited by
Year
Mastering the game of go without human knowledge
D Silver, J Schrittwieser, K Simonyan, I Antonoglou, A Huang, A Guez, ...
nature 550 (7676), 354-359, 2017
116682017
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
D Silver, T Hubert, J Schrittwieser, I Antonoglou, M Lai, A Guez, M Lanctot, ...
Science 362 (6419), 1140-1144, 2018
49522018
Mastering atari, go, chess and shogi by planning with a learned model
J Schrittwieser, I Antonoglou, T Hubert, K Simonyan, L Sifre, S Schmitt, ...
Nature 588 (7839), 604-609, 2020
26342020
Mastering chess and shogi by self-play with a general reinforcement learning algorithm
D Silver, T Hubert, J Schrittwieser, I Antonoglou, M Lai, A Guez, M Lanctot, ...
arXiv preprint arXiv:1712.01815, 2017
24312017
Competition-level code generation with alphacode
Y Li, D Choi, J Chung, N Kushman, J Schrittwieser, R Leblond, T Eccles, ...
Science 378 (6624), 1092-1097, 2022
10122022
Discovering faster matrix multiplication algorithms with reinforcement learning
A Fawzi, M Balog, A Huang, T Hubert, B Romera-Paredes, M Barekatain, ...
Nature 610 (7930), 47-53, 2022
6182022
Cyprien de Masson d’Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J
Y Li, D Choi, J Chung, N Kushman, J Schrittwieser, R Leblond, T Eccles, ...
Science 378 (6624), 1092-1097, 2022
3032022
Faster sorting algorithms discovered using deep reinforcement learning
DJ Mankowitz, A Michi, A Zhernov, M Gelmi, M Selvi, C Paduraru, ...
Nature 618 (7964), 257-263, 2023
1672023
Mastering chess and shogi by self-play with a general reinforcement learning algorithm. arXiv 2017
D Silver, T Hubert, J Schrittwieser, I Antonoglou, M Lai, A Guez, M Lanctot, ...
arXiv preprint arXiv:1712.01815, 2017
1652017
Online and offline reinforcement learning by planning with a learned model
J Schrittwieser, T Hubert, A Mandhane, M Barekatain, I Antonoglou, ...
Advances in Neural Information Processing Systems 34, 27580-27591, 2021
1282021
Learning and planning in complex action spaces
T Hubert, J Schrittwieser, I Antonoglou, M Barekatain, S Schmitt, D Silver
International Conference on Machine Learning, 4476-4486, 2021
912021
Monte-Carlo tree search as regularized policy optimization
JB Grill, F Altché, Y Tang, T Hubert, M Valko, I Antonoglou, R Munos
International Conference on Machine Learning, 3769-3778, 2020
792020
Planning in stochastic environments with a learned model
I Antonoglou, J Schrittwieser, S Ozair, TK Hubert, D Silver
International Conference on Learning Representations, 2021
712021
Approximate exploitability: Learning a best response in large games
F Timbers, N Bard, E Lockhart, M Lanctot, M Schmid, N Burch, ...
arXiv preprint arXiv:2004.09677, 2020
492020
Muzero with self-competition for rate control in vp9 video compression
A Mandhane, A Zhernov, M Rauh, C Gu, M Wang, F Xue, W Shang, ...
arXiv preprint arXiv:2202.06626, 2022
482022
Lai
D Silver, J Schrittwieser, K Simonyan, I Antonoglou, A Huang, A Guez, ...
M., Bolton, A., Chen, Y., Lillicrap, T., Hui, F., Sifre, L., van den, 2017
42017
Adrian Bolton και others
D Silver, J Schrittwieser, K Simonyan, I Antonoglou, A Huang, A Guez, ...
Mastering the game of go without human knowledge. nature 550 (7676), 354-359, 2017
22017
Computer code generation from task descriptions using neural networks
Y Li, DH Choi, J Chung, NA Kushman, J Schrittwieser, R Leblond, ...
US Patent App. 18/105,211, 2023
12023
Optimizing Memory Mapping Using Deep Reinforcement Learning
P Wang, M Sazanovich, B Ilbeyi, PM Phothilimthana, M Purohit, HY Tay, ...
arXiv preprint arXiv:2305.07440, 2023
12023
Planning for agent control using learned hidden states
J Schrittwieser, I Antonoglou, TK Hubert
US Patent App. 17/794,797, 2023
12023
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