Gabriel Dulac-Arnold

40 papers A* 7A 2Journal 26Unranked 5

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	RoboVQA: Multimodal Long-Horizon Reasoning for Robotics. ICRA 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
2024	A	`conf`	The Design of the Barkour Benchmark for Robot Agility. IROS Wenhao Yu, Ken Caluwaerts, Atil Iscen, J. Chase Kew, Tingnan Zhang, Daniel Freeman, Lisa Lee, Stefano Saliceti, Vincent Zhuang, Nathan Batchelor, Steven Bohez, Federico Casarini, José Enrique Chen, Erwin Coumans, Adil Dostmohamed, Gabriel Dulac-Arnold, Alejandro Escontrela, Erik Frey, Roland Hafner, Deepali Jain, Bauyrjan Jyenis, Yuheng Kuang, Tsang-Wei Edward Lee, Ofir Nachum, Ken Oslund, Francesco Romano, Fereshteh Sadeghi, Baruch Tabanpour, Daniel Zheng, Michael Neunert, Raia Hadsell, Nicolas Heess, Francesco Nori, Jeff Seto, Carolina Parada, Vikas Sindhwani, Vincent Vanhoucke, Jie Tan, Kuang-Huei Lee
2023	J	`jnl`	Barkour: Benchmarking Animal-level Agility with Quadruped Robots. CoRR 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, José 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
2023	J	`jnl`	Get Back Here: Robust Imitation by Return-to-Distribution Planning. CoRR Geoffrey Cideron, Baruch Tabanpour, Sebastian Curi, Sertan Girgin, Léonard Hussenot, Gabriel Dulac-Arnold, Matthieu Geist, Olivier Pietquin, Robert Dadashi
2023	A*	`conf`	Investigating the Role of Model-Based Learning in Exploration and Transfer. ICML Jacob C. Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Theophane Weber, Jessica B. Hamrick
2023	J	`jnl`	Investigating the role of model-based learning in exploration and transfer. CoRR Jacob C. Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Théophane Weber, Jessica B. Hamrick
2023	A*	`conf`	Learning Reward Functions for Robotic Manipulation by Observing Humans. ICRA Minttu Alakuijala, Gabriel Dulac-Arnold, Julien Mairal, Jean Ponce, Cordelia Schmid
2023	J	`jnl`	RoboVQA: Multimodal Long-Horizon Reasoning for Robotics. CoRR 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
2022	J	`jnl`	C3PO: Learning to Achieve Arbitrary Goals via Massively Entropic Pretraining. CoRR Alexis Jacq, Manu Orsini, Gabriel Dulac-Arnold, Olivier Pietquin, Matthieu Geist, Olivier Bachem
2022	J	`jnl`	Learning Reward Functions for Robotic Manipulation by Observing Humans. CoRR Minttu Alakuijala, Gabriel Dulac-Arnold, Julien Mairal, Jean Ponce, Cordelia Schmid
2021	J	`jnl`	A Metric Space Perspective on Self-Supervised Policy Adaptation. IEEE Robotics Autom. Lett. Cristian Bodnar, Karol Hausman, Gabriel Dulac-Arnold, Rico Jonschkowski
2021	J	`jnl`	Challenges of real-world reinforcement learning: definitions, benchmarks and analysis. Mach. Learn. Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester
2021	J	`jnl`	Learning Dynamics Models for Model Predictive Agents. CoRR Michael Lutter, Leonard Hasenclever, Arunkumar Byravan, Gabriel Dulac-Arnold, Piotr Trochim, Nicolas Heess, Josh Merel, Yuval Tassa
2021	J	`jnl`	Learning to run a Power Network Challenge: a Retrospective Analysis. CoRR Antoine Marot, Benjamin Donnot, Gabriel Dulac-Arnold, Adrian Kelly, Aïdan O'Sullivan, Jan Viebahn, Mariette Awad, Isabelle Guyon, Patrick Panciatici, Camilo Romero
2021	A*	`conf`	Model-Based Offline Planning. ICLR Arthur Argenson, Gabriel Dulac-Arnold
2021	J	`jnl`	Residual Reinforcement Learning from Demonstrations. CoRR Minttu Alakuijala, Gabriel Dulac-Arnold, Julien Mairal, Jean Ponce, Cordelia Schmid
2020	J	`jnl`	A Geometric Perspective on Self-Supervised Policy Adaptation. CoRR Cristian Bodnar, Karol Hausman, Gabriel Dulac-Arnold, Rico Jonschkowski
2020	J	`jnl`	An empirical investigation of the challenges of real-world reinforcement learning. CoRR Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester
2020	—	`conf`	Learning to run a Power Network Challenge: a Retrospective Analysis. NeurIPS (Competition and Demos) Antoine Marot, Benjamin Donnot, Gabriel Dulac-Arnold, Adrian Kelly, Aidan O'Sullivan, Jan Viebahn, Mariette Awad, Isabelle Guyon, Patrick Panciatici, Camilo Romero
2020	J	`jnl`	Model-Based Offline Planning. CoRR Arthur Argenson, Gabriel Dulac-Arnold
2020	A*	`conf`	RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. NeurIPS 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
2020	J	`jnl`	RL Unplugged: Benchmarks for Offline Reinforcement Learning. CoRR 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
2019	J	`jnl`	Challenges of Real-World Reinforcement Learning. CoRR Gabriel Dulac-Arnold, Daniel J. Mankowitz, Todd Hester
2019	J	`jnl`	Deep multi-class learning from label proportions. CoRR Gabriel Dulac-Arnold, Neil Zeghidour, Marco Cuturi, Lucas Beyer, Jean-Philippe Vert
2019	J	`jnl`	Differentiable Deep Clustering with Cluster Size Constraints. CoRR Aude Genevay, Gabriel Dulac-Arnold, Jean-Philippe Vert
2018	A*	`conf`	Deep Q-learning From Demonstrations. AAAI 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
2017	J	`jnl`	Learning from Demonstrations for Real World Reinforcement Learning. CoRR 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
2017	A*	`conf`	The Predictron: End-To-End Learning and Planning. ICML 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
2016	J	`jnl`	The Predictron: End-To-End Learning and Planning. CoRR 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
2015	J	`jnl`	Deep Reinforcement Learning with Attention for Slate Markov Decision Processes with High-Dimensional States and Actions. CoRR Peter Sunehag, Richard Evans, Gabriel Dulac-Arnold, Yori Zwols, Daniel Visentin, Ben Coppin
2015	J	`jnl`	Reinforcement Learning in Large Discrete Action Spaces. CoRR Gabriel Dulac-Arnold, Richard Evans, Peter Sunehag, Ben Coppin
2014	—	`conf`	Sequentially Generated Instance-Dependent Image Representations for Classification. ICLR Gabriel Dulac-Arnold, Ludovic Denoyer, Nicolas Thome, Matthieu Cord, Patrick Gallinari
2012	—	`conf`	Fast Reinforcement Learning with Large Action Sets Using Error-Correcting Output Codes for MDP Factorization. ECML/PKDD (2) Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari
2012	J	`jnl`	Fast Reinforcement Learning with Large Action Sets using Error-Correcting Output Codes for MDP Factorization CoRR Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari
2012	—	`conf`	Lecture Séquentielle de Documents pour la Classification. CORIA Gabriel Dulac-Arnold, Ludovic Denoyer, Patrick Gallinari
2012	J	`jnl`	Sequential approaches for learning datum-wise sparse representations. Mach. Learn. Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari
2011	J	`jnl`	Datum-Wise Classification: A Sequential Approach to Sparsity CoRR Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari
2011	—	`conf`	Datum-Wise Classification: A Sequential Approach to Sparsity. ECML/PKDD (1) Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari
2011	J	`jnl`	Text Classification: A Sequential Reading Approach CoRR Gabriel Dulac-Arnold, Ludovic Denoyer, Patrick Gallinari
2011	A	`conf`	Text Classification: A Sequential Reading Approach. ECIR Gabriel Dulac-Arnold, Ludovic Denoyer, Patrick Gallinari