Gabriel Barth-Maron
Gabriel Barth-Maron
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Distributed prioritized experience replay
D Horgan, J Quan, D Budden, G Barth-Maron, M Hessel, H Van Hasselt, ...
arXiv preprint arXiv:1803.00933, 2018
Distributed distributional deterministic policy gradients
G Barth-Maron, MW Hoffman, D Budden, W Dabney, D Horgan, D Tb, ...
arXiv preprint arXiv:1804.08617, 2018
Data-efficient deep reinforcement learning for dexterous manipulation
I Popov, N Heess, T Lillicrap, R Hafner, G Barth-Maron, M Vecerik, ...
arXiv preprint arXiv:1704.03073, 2017
Observe and look further: Achieving consistent performance on atari
T Pohlen, B Piot, T Hester, MG Azar, D Horgan, D Budden, G Barth-Maron, ...
arXiv preprint arXiv:1805.11593, 2018
Acme: A research framework for distributed reinforcement learning
M Hoffman, B Shahriari, J Aslanides, G Barth-Maron, F Behbahani, ...
arXiv preprint arXiv:2006.00979, 2020
Goal-based action priors
D Abel, DE Hershkowitz, G Barth-Maron, S Brawner, K O'Farrell, ...
Twenty-Fifth International Conference on Automated Planning and Scheduling, 2015
Making efficient use of demonstrations to solve hard exploration problems
TL Paine, C Gulcehre, B Shahriari, M Denil, M Hoffman, H Soyer, ...
arXiv preprint arXiv:1909.01387, 2019
One-shot high-fidelity imitation: Training large-scale deep nets with rl
TL Paine, SG Colmenarejo, Z Wang, S Reed, Y Aytar, T Pfaff, ...
arXiv preprint arXiv:1810.05017, 2018
Quantized reinforcement learning (quarl)
M Lam, S Chitlangia, S Krishnan, Z Wan, G Barth-Maron, A Faust, ...
arXiv preprint arXiv:1910.01055, 2019
Diego de Las Casas, Andreas Fidjeland, Tim Green, Adrià Puigdomènech, Sébastien Racanière, Jack Rae, and Fabio Viola. Open sourcing Sonnet-a new library for constructing neural …
M Reynolds, G Barth-Maron, F Besse
Affordances as transferable knowledge for planning agents
G Barth-Maron, D Abel, J MacGlashan, S Tellex
2014 AAAI Fall Symposium Series, 2014
Toward affordance-aware planning
D Abel, G Barth-Maron, J MacGlashan, S Tellex
First Workshop on Affordances: Affordances in Vision for Cognitive Robotics, 2014
Making efficient use of demonstrations to solve hard exploration problems
C Gulcehre, T Le Paine, B Shahriari, M Denil, M Hoffman, H Soyer, ...
International Conference on Learning Representations, 2019
Learning deep state representations with convolutional autoencoders
G Barth-Maron
Master’s thesis, Brown University, 2015
Reverb: A Framework For Experience Replay
A Cassirer, G Barth-Maron, E Brevdo, S Ramos, T Boyd, T Sottiaux, ...
arXiv preprint arXiv:2102.04736, 2021
Affordance-Aware Planning
D Abel, G Barth-Maron, J MacGlashan, S Tellex
Reinforcement learning using distributed prioritized replay
D Budden, G Barth-Maron, J Quan, DG Horgan
US Patent App. 16/641,751, 2020
Data-efficient reinforcement learning for continuous control tasks
M Riedmiller, R Hafner, M Vecerik, TP Lillicrap, T Lampe, I Popov, ...
US Patent 10,664,725, 2020
Launchpad: A Programming Model for Distributed Machine Learning Research
F Yang, G Barth-Maron, P Stańczyk, M Hoffman, S Liu, M Kroiss, A Pope, ...
arXiv preprint arXiv:2106.04516, 2021
Distributional reinforcement learning for continuous control tasks
D Budden, MW Hoffman, G Barth-Maron
US Patent App. 16/759,519, 2020
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