Will Dabney
Will Dabney
Verified email at google.com
TitleCited byYear
Rainbow: Combining improvements in deep reinforcement learning
M Hessel, J Modayil, H Van Hasselt, T Schaul, G Ostrovski, W Dabney, ...
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
A distributional perspective on reinforcement learning
MG Bellemare*, W Dabney*, R Munos
arXiv preprint arXiv:1707.06887, 2017
Successor features for transfer in reinforcement learning
A Barreto, W Dabney, R Munos, JJ Hunt, T Schaul, HP van Hasselt, ...
Advances in neural information processing systems, 4055-4065, 2017
The cramer distance as a solution to biased wasserstein gradients
MG Bellemare, I Danihelka, W Dabney, S Mohamed, ...
arXiv preprint arXiv:1705.10743, 2017
Distributed distributional deterministic policy gradients
G Barth-Maron, MW Hoffman, D Budden, W Dabney, D Horgan, A Muldal, ...
arXiv preprint arXiv:1804.08617, 2018
Distributional reinforcement learning with quantile regression
W Dabney, M Rowland, MG Bellemare, R Munos
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Adaptive step-size for online temporal difference learning
W Dabney, AG Barto
Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012
Implicit quantile networks for distributional reinforcement learning
W Dabney, G Ostrovski, D Silver, R Munos
arXiv preprint arXiv:1806.06923, 2018
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
RLPy: a value-function-based reinforcement learning framework for education and research.
A Geramifard, C Dann, RH Klein, W Dabney, JP How
Journal of Machine Learning Research 16 (46), 1573-1578, 2015
Recurrent experience replay in distributed reinforcement learning
S Kapturowski, G Ostrovski, J Quan, R Munos, W Dabney
Utile Distinctions for Relational Reinforcement Learning.
W Dabney, A McGovern
IJCAI 7, 738-743, 2007
Projected natural actor-critic
PS Thomas, WC Dabney, S Giguere, S Mahadevan
Advances in neural information processing systems, 2337-2345, 2013
An analysis of categorical distributional reinforcement learning
M Rowland, MG Bellemare, W Dabney, R Munos, YW Teh
arXiv preprint arXiv:1802.08163, 2018
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
Autoregressive quantile networks for generative modeling
G Ostrovski, W Dabney, R Munos
arXiv preprint arXiv:1806.05575, 2018
Adaptive step-sizes for reinforcement learning
WC Dabney
Natural temporal difference learning
W Dabney, P Thomas
Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014
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
The thing we tried that worked: Utile distinctions for relational reinforcement learning
W Dabney, A McGovern
Proceedings of the ICML-06 Workshop on Open Problems in Statistical …, 2006
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Articles 1–20