Get our free extension to see links to code for papers anywhere online!

 Add to Chrome

 Add to Firefox

CatalyzeX Code Finder - Browser extension linking code for ML papers across the web! | Product Hunt Embed
BYOL works even without batch statistics

Oct 20, 2020
Pierre H. Richemond, Jean-Bastien Grill, Florent Altché, Corentin Tallec, Florian Strub, Andrew Brock, Samuel Smith, Soham De, Razvan Pascanu, Bilal Piot, Michal Valko


  Access Paper or Ask Questions

Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning

Jun 13, 2020
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, Michal Valko


  Access Paper or Ask Questions

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 Gómez Colmenarejo, Serkan Cabi, Caglar Gulcehre, Tom Le Paine, Andrew Cowie, Ziyu Wang, Bilal Piot, Nando de Freitas


  Access Paper or Ask Questions

Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning

Apr 30, 2020
Daniel Guo, Bernardo Avila Pires, Bilal Piot, Jean-bastien Grill, Florent Altché, Rémi Munos, Mohammad Gheshlaghi Azar


  Access Paper or Ask Questions

Agent57: Outperforming the Atari Human Benchmark

Mar 30, 2020
Adrià Puigdomènech Badia, Bilal Piot, Steven Kapturowski, Pablo Sprechmann, Alex Vitvitskyi, Daniel Guo, Charles Blundell


  Access Paper or Ask Questions

Never Give Up: Learning Directed Exploration Strategies

Feb 14, 2020
Adrià Puigdomènech Badia, Pablo Sprechmann, Alex Vitvitskyi, Daniel Guo, Bilal Piot, Steven Kapturowski, Olivier Tieleman, Martín Arjovsky, Alexander Pritzel, Andew Bolt, Charles Blundell

* Published as a conference paper in ICLR 2020 

  Access Paper or Ask Questions

Hindsight Credit Assignment

Dec 05, 2019
Anna Harutyunyan, Will Dabney, Thomas Mesnard, Mohammad Azar, Bilal Piot, Nicolas Heess, Hado van Hasselt, Greg Wayne, Satinder Singh, Doina Precup, Remi Munos

* NeurIPS 2019 

  Access Paper or Ask Questions

World Discovery Models

Mar 01, 2019
Mohammad Gheshlaghi Azar, Bilal Piot, Bernardo Avila Pires, Jean-Bastien Grill, Florent Altché, Rémi Munos


  Access Paper or Ask Questions

Neural Predictive Belief Representations

Nov 15, 2018
Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Bernardo A. Pires, Toby Pohlen, Rémi Munos


  Access Paper or Ask Questions

Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards

Oct 08, 2018
Mel Vecerik, Todd Hester, Jonathan Scholz, Fumin Wang, Olivier Pietquin, Bilal Piot, Nicolas Heess, Thomas Rothörl, Thomas Lampe, Martin Riedmiller


  Access Paper or Ask Questions

Playing the Game of Universal Adversarial Perturbations

Sep 25, 2018
Julien Perolat, Mateusz Malinowski, Bilal Piot, Olivier Pietquin


  Access Paper or Ask Questions

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 Večerík, Matteo Hessel, Rémi Munos, Olivier Pietquin


  Access Paper or Ask Questions

Noisy Networks for Exploration

Feb 15, 2018
Meire Fortunato, Mohammad Gheshlaghi Azar, Bilal Piot, Jacob Menick, Ian Osband, Alex Graves, Vlad Mnih, Remi Munos, Demis Hassabis, Olivier Pietquin, Charles Blundell, Shane Legg

* ICLR 2018 

  Access Paper or Ask Questions

Is the Bellman residual a bad proxy?

Dec 12, 2017
Matthieu Geist, Bilal Piot, Olivier Pietquin

* Final NIPS 2017 version (title, among other things, changed) 

  Access Paper or Ask Questions

Deep Q-learning from Demonstrations

Nov 22, 2017
Todd Hester, Matej Vecerik, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Dan Horgan, John Quan, Andrew Sendonaris, Gabriel Dulac-Arnold, Ian Osband, John Agapiou, Joel Z. Leibo, Audrunas Gruslys

* Published at AAAI 2018. Previously on arxiv as "Learning from Demonstrations for Real World Reinforcement Learning" 

  Access Paper or Ask Questions

Rainbow: Combining Improvements in Deep Reinforcement Learning

Oct 06, 2017
Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Azar, David Silver

* Under review as a conference paper at AAAI 2018 

  Access Paper or Ask Questions

Observational Learning by Reinforcement Learning

Jun 20, 2017
Diana Borsa, Bilal Piot, Rémi Munos, Olivier Pietquin


  Access Paper or Ask Questions

End-to-end optimization of goal-driven and visually grounded dialogue systems

Mar 15, 2017
Florian Strub, Harm de Vries, Jeremie Mary, Bilal Piot, Aaron Courville, Olivier Pietquin


  Access Paper or Ask Questions

Difference of Convex Functions Programming Applied to Control with Expert Data

Sep 05, 2016
Bilal Piot, Matthieu Geist, Olivier Pietquin


  Access Paper or Ask Questions