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RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning

Nov 04, 2021
Sabela Ramos, Sertan Girgin, Léonard Hussenot, Damien Vincent, Hanna Yakubovich, Daniel Toyama, Anita Gergely, Piotr Stanczyk, Raphael Marinier, Jeremiah Harmsen, Olivier Pietquin, Nikola Momchev


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Continuous Control with Action Quantization from Demonstrations

Oct 19, 2021
Robert Dadashi, Léonard Hussenot, Damien Vincent, Sertan Girgin, Anton Raichuk, Matthieu Geist, Olivier Pietquin

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What Matters for Adversarial Imitation Learning?

Jun 01, 2021
Manu Orsini, Anton Raichuk, Léonard Hussenot, Damien Vincent, Robert Dadashi, Sertan Girgin, Matthieu Geist, Olivier Bachem, Olivier Pietquin, Marcin Andrychowicz

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Hyperparameter Selection for Imitation Learning

May 25, 2021
Leonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Lukasz Stafiniak, Sertan Girgin, Raphael Marinier, Nikola Momchev, Sabela Ramos, Manu Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin

* ICML 2021 

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Google Research Football: A Novel Reinforcement Learning Environment

Jul 25, 2019
Karol Kurach, Anton Raichuk, Piotr Stańczyk, Michał Zając, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly

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MULEX: Disentangling Exploitation from Exploration in Deep RL

Jul 01, 2019
Lucas Beyer, Damien Vincent, Olivier Teboul, Sylvain Gelly, Matthieu Geist, Olivier Pietquin

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Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates

Jun 19, 2019
Hugo Penedones, Carlos Riquelme, Damien Vincent, Hartmut Maennel, Timothy Mann, Andre Barreto, Sylvain Gelly, Gergely Neu

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Episodic Curiosity through Reachability

Feb 22, 2019
Nikolay Savinov, Anton Raichuk, Raphaël Marinier, Damien Vincent, Marc Pollefeys, Timothy Lillicrap, Sylvain Gelly

* Accepted to ICLR 2019. Code at Videos at 

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Clustering Meets Implicit Generative Models

Aug 02, 2018
Francesco Locatello, Damien Vincent, Ilya Tolstikhin, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf

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Temporal Difference Learning with Neural Networks - Study of the Leakage Propagation Problem

Jul 09, 2018
Hugo Penedones, Damien Vincent, Hartmut Maennel, Sylvain Gelly, Timothy Mann, Andre Barreto

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Spatially adaptive image compression using a tiled deep network

Feb 07, 2018
David Minnen, George Toderici, Michele Covell, Troy Chinen, Nick Johnston, Joel Shor, Sung Jin Hwang, Damien Vincent, Saurabh Singh

* International Conference on Image Processing 2017 

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Full Resolution Image Compression with Recurrent Neural Networks

Jul 07, 2017
George Toderici, Damien Vincent, Nick Johnston, Sung Jin Hwang, David Minnen, Joel Shor, Michele Covell

* Updated with content for CVPR and removed supplemental material to an external link for size limitations 

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Toward Optimal Run Racing: Application to Deep Learning Calibration

Jun 20, 2017
Olivier Bousquet, Sylvain Gelly, Karol Kurach, Marc Schoenauer, Michele Sebag, Olivier Teytaud, Damien Vincent

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Critical Hyper-Parameters: No Random, No Cry

Jun 10, 2017
Olivier Bousquet, Sylvain Gelly, Karol Kurach, Olivier Teytaud, Damien Vincent

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Better Text Understanding Through Image-To-Text Transfer

May 26, 2017
Karol Kurach, Sylvain Gelly, Michal Jastrzebski, Philip Haeusser, Olivier Teytaud, Damien Vincent, Olivier Bousquet

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Target-Quality Image Compression with Recurrent, Convolutional Neural Networks

May 18, 2017
Michele Covell, Nick Johnston, David Minnen, Sung Jin Hwang, Joel Shor, Saurabh Singh, Damien Vincent, George Toderici

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Improved Lossy Image Compression with Priming and Spatially Adaptive Bit Rates for Recurrent Networks

Mar 29, 2017
Nick Johnston, Damien Vincent, David Minnen, Michele Covell, Saurabh Singh, Troy Chinen, Sung Jin Hwang, Joel Shor, George Toderici

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Variable Rate Image Compression with Recurrent Neural Networks

Mar 01, 2016
George Toderici, Sean M. O'Malley, Sung Jin Hwang, Damien Vincent, David Minnen, Shumeet Baluja, Michele Covell, Rahul Sukthankar

* Under review as a conference paper at ICLR 2016 

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