Dulac-Arnold, Gabriel

13 publications

ICML 2023 Investigating the Role of Model-Based Learning in Exploration and Transfer Jacob C Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Theophane Weber, Jessica B Hamrick

NeurIPSW 2023 On the Importance of Data Collection for Training General Goal-Reaching Policies. Alexis D. Jacq, Manu Orsini, Gabriel Dulac-Arnold, Olivier Pietquin, Matthieu Geist, Olivier Bachem

NeurIPSW 2023 RoboVQA: Multimodal Long-Horizon Reasoningfor Robotics Pierre Sermanet, Tianli Ding, Jeffrey Zhao, Fei Xia, Debidatta Dwibedi, Keerthana Gopalakrishnan, Christine Chan, Gabriel Dulac-Arnold, Sharath Maddineni, Nikhil Joshi, Pete Florence, Wei Han, Robert Baruch, Yao Lu, Suvir Mirchandani, Peng Xu, Pannag Sanketi, Karol Hausman, Izhak Shafran, Brian Ichter, Yuan Cao

MLJ 2021 Challenges of Real-World Reinforcement Learning: Definitions, Benchmarks and Analysis Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester

ICLR 2021 Model-Based Offline Planning Arthur Argenson, Gabriel Dulac-Arnold

NeurIPS 2020 RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez, Konrad Zolna, Rishabh Agarwal, Josh S Merel, Daniel J Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas

ICMLW 2019 Challenges of Real-World Reinforcement Learning Gabriel Dulac-Arnold, Daniel Mankowitz, Todd Hester

AAAI 2018 Deep Q-Learning from Demonstrations Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Dan Horgan, John Quan, Andrew Sendonaris, Ian Osband, Gabriel Dulac-Arnold, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys

ICML 2017 The Predictron: End-to-End Learning and Planning David Silver, Hado Hasselt, Matteo Hessel, Tom Schaul, Arthur Guez, Tim Harley, Gabriel Dulac-Arnold, David Reichert, Neil Rabinowitz, Andre Barreto, Thomas Degris

ICLR 2014 Sequentially Generated Instance-Dependent Image Representations for Classification Gabriel Dulac-Arnold, Ludovic Denoyer, Nicolas Thome, Matthieu Cord, Patrick Gallinari

ECML-PKDD 2012 Fast Reinforcement Learning with Large Action Sets Using Error-Correcting Output Codes for MDP Factorization Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari

MLJ 2012 Sequential Approaches for Learning Datum-Wise Sparse Representations Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari

ECML-PKDD 2011 Datum-Wise Classification: A Sequential Approach to Sparsity Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari