publications

publications by categories in reversed chronological order. generated by jekyll-scholar.

2017

  1. Data-efficient deep reinforcement learning for dexterous manipulation
    Ivaylo Popov, Nicolas Heess, Timothy Lillicrap, Roland Hafner, Gabriel Barth-Maron, Matej Vecerik, and 4 more authors
    arXiv preprint arXiv:1704.03073 2017
  2. 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 networks
    Malcolm Reynolds, Gabriel Barth-Maron, and Frederic Besse
    2017

2018

  1. Distributed prioritized experience replay
    Dan Horgan, John Quan, David Budden, Gabriel Barth-Maron, Matteo Hessel, Hado Van Hasselt, and 1 more author
    arXiv preprint arXiv:1803.00933 2018
  2. Distributed distributional deterministic policy gradients
    Gabriel Barth-Maron, Matthew W Hoffman, David Budden, Will Dabney, Dan Horgan, Dhruva Tb, and 3 more authors
    arXiv preprint arXiv:1804.08617 2018
  3. Observe and look further: Achieving consistent performance on atari
    Tobias Pohlen, Bilal Piot, Todd Hester, Mohammad Gheshlaghi Azar, Dan Horgan, David Budden, and 5 more authors
    arXiv preprint arXiv:1805.11593 2018
  4. One-shot high-fidelity imitation: Training large-scale deep nets with rl
    Tom Le Paine, Sergio Gómez Colmenarejo, Ziyu Wang, Scott Reed, Yusuf Aytar, Tobias Pfaff, and 5 more authors
    arXiv preprint arXiv:1810.05017 2018
  5. Towards Consistent Performance on Atari using Expert Demonstrations
    Tobias Pohlen, Bilal Piot, Todd Hester, Mohammad Gheshlaghi Azar, Dan Horgan, David Budden, and 5 more authors
    2018

2019

  1. Making efficient use of demonstrations to solve hard exploration problems
    Tom Le Paine, Caglar Gulcehre, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, and 5 more authors
    arXiv preprint arXiv:1909.01387 2019
  2. Quantized reinforcement learning (quarl)
    Maximilian Lam, Sharad Chitlangia, Srivatsan Krishnan, Zishen Wan, Gabriel Barth-Maron, Aleksandra Faust, and 1 more author
    arXiv preprint arXiv:1910.01055 2019
  3. Making efficient use of demonstrations to solve hard exploration problems
    Caglar Gulcehre, Tom Le Paine, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, and 5 more authors
    2019
  4. QuaRL: Quantization for sustainable reinforcement learning
    Srivatsan Krishnan, Maximilian Lam, Sharad Chitlangia, Zishen Wan, Gabriel Barth-Maron, Aleksandra Faust, and 1 more author
    arXiv e-prints 2019
  5. Making efficient use of demonstrations to solve hard exploration problems
    Tom Le Paine, Caglar Gulcehre, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, and 5 more authors
    arXiv e-prints 2019

2020

  1. Acme: A research framework for distributed reinforcement learning
    Matt Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron, Feryal Behbahani, Tamara Norman, and 5 more authors
    arXiv preprint arXiv:2006.00979 2020

2021

  1. Reverb: a framework for experience replay
    Albin Cassirer, Gabriel Barth-Maron, Eugene Brevdo, Sabela Ramos, Toby Boyd, Thibault Sottiaux, and 1 more author
    arXiv preprint arXiv:2102.04736 2021
  2. Launchpad: a programming model for distributed machine learning research
    Fan Yang, Gabriel Barth-Maron, Piotr Stańczyk, Matthew Hoffman, Siqi Liu, Manuel Kroiss, and 2 more authors
    arXiv preprint arXiv:2106.04516 2021

2022

  1. A Generalist Agent
    Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, and 5 more authors
    arXiv preprint arXiv:2205.06175 2022