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Launchpad: A Programming Model for Distributed Machine Learning Research


Jun 07, 2021
Fan Yang, Gabriel Barth-Maron, Piotr Sta艅czyk, Matthew Hoffman, Siqi Liu, Manuel Kroiss, Aedan Pope, Alban Rrustemi


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Reverb: A Framework For Experience Replay


Feb 09, 2021
Albin Cassirer, Gabriel Barth-Maron, Eugene Brevdo, Sabela Ramos, Toby Boyd, Thibault Sottiaux, Manuel Kroiss

* 11 pages 

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Acme: A Research Framework for Distributed Reinforcement Learning


Jun 01, 2020
Matt Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron, Feryal Behbahani, Tamara Norman, Abbas Abdolmaleki, Albin Cassirer, Fan Yang, Kate Baumli, Sarah Henderson, Alex Novikov, Sergio G贸mez Colmenarejo, Serkan Cabi, Caglar Gulcehre, Tom Le Paine, Andrew Cowie, Ziyu Wang, Bilal Piot, Nando de Freitas


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Making Efficient Use of Demonstrations to Solve Hard Exploration Problems


Sep 03, 2019
Tom Le Paine, Caglar Gulcehre, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil Rabinowitz, Duncan Williams, Gabriel Barth-Maron, Ziyu Wang, Nando de Freitas, Worlds Team


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One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL


Oct 11, 2018
Tom Le Paine, Sergio G贸mez Colmenarejo, Ziyu Wang, Scott Reed, Yusuf Aytar, Tobias Pfaff, Matt W. Hoffman, Gabriel Barth-Maron, Serkan Cabi, David Budden, Nando de Freitas


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Observe and Look Further: Achieving Consistent Performance on Atari


May 29, 2018
Tobias Pohlen, Bilal Piot, Todd Hester, Mohammad Gheshlaghi Azar, Dan Horgan, David Budden, Gabriel Barth-Maron, Hado van Hasselt, John Quan, Mel Ve膷er铆k, Matteo Hessel, R茅mi Munos, Olivier Pietquin


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Distributed Distributional Deterministic Policy Gradients


Apr 23, 2018
Gabriel Barth-Maron, Matthew W. Hoffman, David Budden, Will Dabney, Dan Horgan, Dhruva TB, Alistair Muldal, Nicolas Heess, Timothy Lillicrap


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Distributed Prioritized Experience Replay


Mar 02, 2018
Dan Horgan, John Quan, David Budden, Gabriel Barth-Maron, Matteo Hessel, Hado van Hasselt, David Silver

* Accepted to International Conference on Learning Representations 2018 

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Data-efficient Deep Reinforcement Learning for Dexterous Manipulation


Apr 10, 2017
Ivaylo Popov, Nicolas Heess, Timothy Lillicrap, Roland Hafner, Gabriel Barth-Maron, Matej Vecerik, Thomas Lampe, Yuval Tassa, Tom Erez, Martin Riedmiller

* 12 pages, 5 Figures 

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