Segui
Ioannis Antonoglou
Ioannis Antonoglou
Deepmind, UCL
Email verificata su reflection.ai
Titolo
Citata da
Citata da
Anno
Human-level control through deep reinforcement learning
V Mnih, K Kavukcuoglu, D Silver, AA Rusu, J Veness, MG Bellemare, ...
nature 518 (7540), 529-533, 2015
327212015
Mastering the game of Go with deep neural networks and tree search
D Silver, A Huang, CJ Maddison, A Guez, L Sifre, G Van Den Driessche, ...
nature 529 (7587), 484-489, 2016
203882016
Playing atari with deep reinforcement learning
V Mnih
arXiv preprint arXiv:1312.5602, 2013
162912013
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
116012017
Prioritized Experience Replay
T Schaul
arXiv preprint arXiv:1511.05952, 2015
52092015
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
49092018
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
26112020
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
24112017
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
20702023
Playing atari with deep reinforcement learning. arXiv 2013
V Mnih, K Kavukcuoglu, D Silver, A Graves, I Antonoglou, D Wierstra, ...
arXiv preprint arXiv:1312.5602, 2013
10602013
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ...
arXiv preprint arXiv:2403.05530, 2024
6142024
Gemini: A family of highly capable multimodal models
R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ...
arXiv preprint arXiv:2312.11805 1, 2023
2172023
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
1622017
Bayesian optimization in alphago
Y Chen, A Huang, Z Wang, I Antonoglou, J Schrittwieser, D Silver, ...
arXiv preprint arXiv:1812.06855, 2018
1602018
Prioritized experience replay. arXiv 2015
T Schaul, J Quan, I Antonoglou, D Silver
arXiv preprint arXiv:1511.05952 5952, 2016
1542016
Unit tests for stochastic optimization
T Schaul, I Antonoglou, D Silver
arXiv preprint arXiv:1312.6055, 2013
1402013
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
1242021
Learning to search with mctsnets
A Guez, T Weber, I Antonoglou, K Simonyan, O Vinyals, D Wierstra, ...
International conference on machine learning, 1822-1831, 2018
972018
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
A test of relative similarity for model selection in generative models
W Bounliphone, E Belilovsky, MB Blaschko, I Antonoglou, A Gretton
arXiv preprint arXiv:1511.04581, 2015
872015
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
Articoli 1–20