Gabriel Dulac-Arnold

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 30

Top Topics

Supervised Clustering

Markov Decision Process

Reinforcement Learning

Top Venues

Publications

Pierre Sermanet, Tianli Ding, Jeffrey Zhao, Fei Xia, Debidatta Dwibedi, Keerthana Gopalakrishnan, Christine Chan, Gabriel Dulac-Arnold, Sharath Maddineni, Nikhil J. Joshi, Pete Florence, Wei Han, Robert Baruch, Yao Lu, Suvir Mirchandani, Peng Xu, Pannag Sanketi, Karol Hausman, Izhak Shafran, Brian Ichter, Yuan Cao
RoboVQA: Multimodal Long-Horizon Reasoning for Robotics. ICRA (2024)
Geoffrey Cideron, Baruch Tabanpour, Sebastian Curi, Sertan Girgin, Léonard Hussenot, Gabriel Dulac-Arnold, Matthieu Geist, Olivier Pietquin, Robert Dadashi
Get Back Here: Robust Imitation by Return-to-Distribution Planning. CoRR (2023)
Pierre Sermanet, Tianli Ding, Jeffrey Zhao, Fei Xia, Debidatta Dwibedi, Keerthana Gopalakrishnan, Christine Chan, Gabriel Dulac-Arnold, Sharath Maddineni, Nikhil J. Joshi, Pete Florence, Wei Han, Robert Baruch, Yao Lu, Suvir Mirchandani, Peng Xu, Pannag Sanketi, Karol Hausman, Izhak Shafran, Brian Ichter, Yuan Cao
RoboVQA: Multimodal Long-Horizon Reasoning for Robotics. CoRR (2023)
Ken Caluwaerts, Atil Iscen, J. Chase Kew, Wenhao Yu, Tingnan Zhang, Daniel Freeman, Kuang-Huei Lee, Lisa Lee, Stefano Saliceti, Vincent Zhuang, Nathan Batchelor, Steven Bohez, Federico Casarini, Jose Enrique Chen, Omar Cortes, Erwin Coumans, Adil Dostmohamed, Gabriel Dulac-Arnold, Alejandro Escontrela, Erik Frey, Roland Hafner, Deepali Jain, Bauyrjan Jyenis, Yuheng Kuang, Tsang-Wei Edward Lee, Linda Luu, Ofir Nachum, Ken Oslund, Jason Powell, Diego Reyes, Francesco Romano, Fereshteh Sadeghi, Ron Sloat, Baruch Tabanpour, Daniel Zheng, Michael Neunert, Raia Hadsell, Nicolas Heess, Francesco Nori, Jeff Seto, Carolina Parada, Vikas Sindhwani, Vincent Vanhoucke, Jie Tan
Barkour: Benchmarking Animal-level Agility with Quadruped Robots. CoRR (2023)
Minttu Alakuijala, Gabriel Dulac-Arnold, Julien Mairal, Jean Ponce, Cordelia Schmid
Learning Reward Functions for Robotic Manipulation by Observing Humans. ICRA (2023)
Jacob C. Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Théophane Weber, Jessica B. Hamrick
Investigating the role of model-based learning in exploration and transfer. CoRR (2023)
Jacob C. Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Theophane Weber, Jessica B. Hamrick
Investigating the Role of Model-Based Learning in Exploration and Transfer. ICML (2023)
Alexis Jacq, Manu Orsini, Gabriel Dulac-Arnold, Olivier Pietquin, Matthieu Geist, Olivier Bachem
C3PO: Learning to Achieve Arbitrary Goals via Massively Entropic Pretraining. CoRR (2022)
Minttu Alakuijala, Gabriel Dulac-Arnold, Julien Mairal, Jean Ponce, Cordelia Schmid
Learning Reward Functions for Robotic Manipulation by Observing Humans. CoRR (2022)
Michael Lutter, Leonard Hasenclever, Arunkumar Byravan, Gabriel Dulac-Arnold, Piotr Trochim, Nicolas Heess, Josh Merel, Yuval Tassa
Learning Dynamics Models for Model Predictive Agents. CoRR (2021)
Cristian Bodnar, Karol Hausman, Gabriel Dulac-Arnold, Rico Jonschkowski
A Metric Space Perspective on Self-Supervised Policy Adaptation. IEEE Robotics Autom. Lett. 6 (3) (2021)
Antoine Marot, Benjamin Donnot, Gabriel Dulac-Arnold, Adrian Kelly, Aïdan O'Sullivan, Jan Viebahn, Mariette Awad, Isabelle Guyon, Patrick Panciatici, Camilo Romero
Learning to run a Power Network Challenge: a Retrospective Analysis. CoRR (2021)
Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester
Challenges of real-world reinforcement learning: definitions, benchmarks and analysis. Mach. Learn. 110 (9) (2021)
Arthur Argenson, Gabriel Dulac-Arnold
Model-Based Offline Planning. ICLR (2021)
Minttu Alakuijala, Gabriel Dulac-Arnold, Julien Mairal, Jean Ponce, Cordelia Schmid
Residual Reinforcement Learning from Demonstrations. CoRR (2021)
Arthur Argenson, Gabriel Dulac-Arnold
Model-Based Offline Planning. CoRR (2020)
Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas
RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. NeurIPS (2020)
Cristian Bodnar, Karol Hausman, Gabriel Dulac-Arnold, Rico Jonschkowski
A Geometric Perspective on Self-Supervised Policy Adaptation. CoRR (2020)
Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas
RL Unplugged: Benchmarks for Offline Reinforcement Learning. CoRR (2020)
Antoine Marot, Benjamin Donnot, Gabriel Dulac-Arnold, Adrian Kelly, Aidan O'Sullivan, Jan Viebahn, Mariette Awad, Isabelle Guyon, Patrick Panciatici, Camilo Romero
Learning to run a Power Network Challenge: a Retrospective Analysis. NeurIPS (Competition and Demos) (2020)
Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester
An empirical investigation of the challenges of real-world reinforcement learning. CoRR (2020)
Gabriel Dulac-Arnold, Daniel J. Mankowitz, Todd Hester
Challenges of Real-World Reinforcement Learning. CoRR (2019)
Gabriel Dulac-Arnold, Neil Zeghidour, Marco Cuturi, Lucas Beyer, Jean-Philippe Vert
Deep multi-class learning from label proportions. CoRR (2019)
Aude Genevay, Gabriel Dulac-Arnold, Jean-Philippe Vert
Differentiable Deep Clustering with Cluster Size Constraints. CoRR (2019)
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
Deep Q-learning From Demonstrations. AAAI (2018)
Todd Hester, Matej Vecerík, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Andrew Sendonaris, Gabriel Dulac-Arnold, Ian Osband, John P. Agapiou, Joel Z. Leibo, Audrunas Gruslys
Learning from Demonstrations for Real World Reinforcement Learning. CoRR (2017)
David Silver, Hado van Hasselt, Matteo Hessel, Tom Schaul, Arthur Guez, Tim Harley, Gabriel Dulac-Arnold, David P. Reichert, Neil C. Rabinowitz, André Barreto, Thomas Degris
The Predictron: End-To-End Learning and Planning. ICML (2017)
David Silver, Hado van Hasselt, Matteo Hessel, Tom Schaul, Arthur Guez, Tim Harley, Gabriel Dulac-Arnold, David P. Reichert, Neil C. Rabinowitz, André Barreto, Thomas Degris
The Predictron: End-To-End Learning and Planning. CoRR (2016)
Gabriel Dulac-Arnold, Richard Evans, Peter Sunehag, Ben Coppin
Reinforcement Learning in Large Discrete Action Spaces. CoRR (2015)
Peter Sunehag, Richard Evans, Gabriel Dulac-Arnold, Yori Zwols, Daniel Visentin, Ben Coppin
Deep Reinforcement Learning with Attention for Slate Markov Decision Processes with High-Dimensional States and Actions. CoRR (2015)
Gabriel Dulac-Arnold, Ludovic Denoyer, Nicolas Thome, Matthieu Cord, Patrick Gallinari
Sequentially Generated Instance-Dependent Image Representations for Classification. ICLR (2014)
Gabriel Dulac-Arnold, Ludovic Denoyer, Patrick Gallinari
Lecture Séquentielle de Documents pour la Classification. CORIA (2012)
Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari
Sequential approaches for learning datum-wise sparse representations. Mach. Learn. 89 (1-2) (2012)
Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari
Fast Reinforcement Learning with Large Action Sets using Error-Correcting Output Codes for MDP Factorization CoRR (2012)
Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari
Fast Reinforcement Learning with Large Action Sets Using Error-Correcting Output Codes for MDP Factorization. ECML/PKDD (2) (2012)
Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari
Datum-Wise Classification: A Sequential Approach to Sparsity CoRR (2011)
Gabriel Dulac-Arnold, Ludovic Denoyer, Patrick Gallinari
Text Classification: A Sequential Reading Approach. ECIR (2011)
Gabriel Dulac-Arnold, Ludovic Denoyer, Patrick Gallinari
Text Classification: A Sequential Reading Approach CoRR (2011)
Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari
Datum-Wise Classification: A Sequential Approach to Sparsity. ECML/PKDD (1) (2011)