Will Dabney
Will Dabney
DeepMind
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Rainbow: Combining improvements in deep reinforcement learning
M Hessel, J Modayil, H Van Hasselt, T Schaul, G Ostrovski, W Dabney, ...
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
9012018
A distributional perspective on reinforcement learning
MG Bellemare*, W Dabney*, R Munos
arXiv preprint arXiv:1707.06887, 2017
5992017
Successor features for transfer in reinforcement learning
A Barreto, W Dabney, R Munos, JJ Hunt, T Schaul, H Van Hasselt, ...
arXiv preprint arXiv:1606.05312, 2016
2552016
Distributed distributional deterministic policy gradients
G Barth-Maron, MW Hoffman, D Budden, W Dabney, D Horgan, D Tb, ...
arXiv preprint arXiv:1804.08617, 2018
2312018
Distributional reinforcement learning with quantile regression
W Dabney, M Rowland, M Bellemare, R Munos
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
1882018
The cramer distance as a solution to biased wasserstein gradients
MG Bellemare, I Danihelka, W Dabney, S Mohamed, ...
arXiv preprint arXiv:1705.10743, 2017
1852017
Implicit quantile networks for distributional reinforcement learning
W Dabney, G Ostrovski, D Silver, R Munos
International conference on machine learning, 1096-1105, 2018
1392018
Recurrent experience replay in distributed reinforcement learning
S Kapturowski, G Ostrovski, J Quan, R Munos, W Dabney
International conference on learning representations, 2018
1362018
A distributional code for value in dopamine-based reinforcement learning
W Dabney, Z Kurth-Nelson, N Uchida, CK Starkweather, D Hassabis, ...
Nature 577 (7792), 671-675, 2020
922020
Adaptive step-size for online temporal difference learning
W Dabney, A Barto
Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 2012
512012
An analysis of categorical distributional reinforcement learning
M Rowland, M Bellemare, W Dabney, R Munos, YW Teh
International Conference on Artificial Intelligence and Statistics, 29-37, 2018
502018
RLPy: a value-function-based reinforcement learning framework for education and research.
A Geramifard, C Dann, RH Klein, W Dabney, JP How
J. Mach. Learn. Res. 16 (1), 1573-1578, 2015
432015
The reactor: A fast and sample-efficient actor-critic agent for reinforcement learning
A Gruslys, W Dabney, MG Azar, B Piot, M Bellemare, R Munos
arXiv preprint arXiv:1704.04651, 2017
422017
Autoregressive quantile networks for generative modeling
G Ostrovski, W Dabney, R Munos
International Conference on Machine Learning, 3936-3945, 2018
412018
Proximal reinforcement learning: A new theory of sequential decision making in primal-dual spaces
S Mahadevan, B Liu, P Thomas, W Dabney, S Giguere, N Jacek, I Gemp, ...
arXiv preprint arXiv:1405.6757, 2014
372014
A geometric perspective on optimal representations for reinforcement learning
MG Bellemare, W Dabney, R Dadashi, AA Taiga, PS Castro, NL Roux, ...
arXiv preprint arXiv:1901.11530, 2019
342019
Projected Natural Actor-Critic.
PS Thomas, W Dabney, S Giguere, S Mahadevan
NIPS, 2337-2345, 2013
262013
Utile Distinctions for Relational Reinforcement Learning.
W Dabney, A McGovern
IJCAI 7, 738-743, 2007
212007
Deep reinforcement learning and its neuroscientific implications
M Botvinick, JX Wang, W Dabney, KJ Miller, Z Kurth-Nelson
Neuron, 2020
202020
Statistics and samples in distributional reinforcement learning
M Rowland, R Dadashi, S Kumar, R Munos, MG Bellemare, W Dabney
International Conference on Machine Learning, 5528-5536, 2019
202019
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Articles 1–20