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Gabriel Dulac-Arnold

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Learning Reward Functions for Robotic Manipulation by Observing Humans


Nov 16, 2022
Minttu Alakuijala, Gabriel Dulac-Arnold, Julien Mairal, Jean Ponce, Cordelia Schmid

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C3PO: Learning to Achieve Arbitrary Goals via Massively Entropic Pretraining


Nov 07, 2022
Alexis Jacq, Manu Orsini, Gabriel Dulac-Arnold, Olivier Pietquin, Matthieu Geist, Olivier Bachem

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Learning Dynamics Models for Model Predictive Agents


Sep 29, 2021
Michael Lutter, Leonard Hasenclever, Arunkumar Byravan, Gabriel Dulac-Arnold, Piotr Trochim, Nicolas Heess, Josh Merel, Yuval Tassa

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Residual Reinforcement Learning from Demonstrations


Jun 15, 2021
Minttu Alakuijala, Gabriel Dulac-Arnold, Julien Mairal, Jean Ponce, Cordelia Schmid

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Learning to run a Power Network Challenge: a Retrospective Analysis


Mar 02, 2021
Antoine Marot, Benjamin Donnot, Gabriel Dulac-Arnold, Adrian Kelly, Aïdan O'Sullivan, Jan Viebahn, Mariette Awad, Isabelle Guyon, Patrick Panciatici, Camilo Romero

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A Geometric Perspective on Self-Supervised Policy Adaptation


Nov 14, 2020
Cristian Bodnar, Karol Hausman, Gabriel Dulac-Arnold, Rico Jonschkowski

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* Contains 17 pages, 18 figures 

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Model-Based Offline Planning


Aug 12, 2020
Arthur Argenson, Gabriel Dulac-Arnold

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RL Unplugged: Benchmarks for Offline Reinforcement Learning


Jul 02, 2020
Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gomez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas

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* 21 pages including supplementary material, the github link for the datasets: https://github.com/deepmind/deepmind-research/rl_unplugged 

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An empirical investigation of the challenges of real-world reinforcement learning


Mar 24, 2020
Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester

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* arXiv admin note: text overlap with arXiv:1904.12901 

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