Alert button
Picture for Gabriel Dulac-Arnold

Gabriel Dulac-Arnold

Alert button

Model-Based Offline Planning

Aug 12, 2020
Arthur Argenson, Gabriel Dulac-Arnold

Figure 1 for Model-Based Offline Planning
Figure 2 for Model-Based Offline Planning
Figure 3 for Model-Based Offline Planning
Figure 4 for Model-Based Offline Planning
Viaarxiv icon

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

Figure 1 for RL Unplugged: Benchmarks for Offline Reinforcement Learning
Figure 2 for RL Unplugged: Benchmarks for Offline Reinforcement Learning
Figure 3 for RL Unplugged: Benchmarks for Offline Reinforcement Learning
Figure 4 for RL Unplugged: Benchmarks for Offline Reinforcement Learning
Viaarxiv icon

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

Figure 1 for An empirical investigation of the challenges of real-world reinforcement learning
Figure 2 for An empirical investigation of the challenges of real-world reinforcement learning
Figure 3 for An empirical investigation of the challenges of real-world reinforcement learning
Figure 4 for An empirical investigation of the challenges of real-world reinforcement learning
Viaarxiv icon

Differentiable Deep Clustering with Cluster Size Constraints

Oct 20, 2019
Aude Genevay, Gabriel Dulac-Arnold, Jean-Philippe Vert

Figure 1 for Differentiable Deep Clustering with Cluster Size Constraints
Figure 2 for Differentiable Deep Clustering with Cluster Size Constraints
Figure 3 for Differentiable Deep Clustering with Cluster Size Constraints
Viaarxiv icon

Deep multi-class learning from label proportions

May 30, 2019
Gabriel Dulac-Arnold, Neil Zeghidour, Marco Cuturi, Lucas Beyer, Jean-Philippe Vert

Figure 1 for Deep multi-class learning from label proportions
Figure 2 for Deep multi-class learning from label proportions
Viaarxiv icon

Challenges of Real-World Reinforcement Learning

Apr 29, 2019
Gabriel Dulac-Arnold, Daniel Mankowitz, Todd Hester

Figure 1 for Challenges of Real-World Reinforcement Learning
Figure 2 for Challenges of Real-World Reinforcement Learning
Figure 3 for Challenges of Real-World Reinforcement Learning
Figure 4 for Challenges of Real-World Reinforcement Learning
Viaarxiv icon

Deep Q-learning from Demonstrations

Nov 22, 2017
Todd Hester, Matej Vecerik, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Dan Horgan, John Quan, Andrew Sendonaris, Gabriel Dulac-Arnold, Ian Osband, John Agapiou, Joel Z. Leibo, Audrunas Gruslys

Figure 1 for Deep Q-learning from Demonstrations
Figure 2 for Deep Q-learning from Demonstrations
Figure 3 for Deep Q-learning from Demonstrations
Viaarxiv icon

The Predictron: End-To-End Learning and Planning

Jul 20, 2017
David Silver, Hado van Hasselt, Matteo Hessel, Tom Schaul, Arthur Guez, Tim Harley, Gabriel Dulac-Arnold, David Reichert, Neil Rabinowitz, Andre Barreto, Thomas Degris

Figure 1 for The Predictron: End-To-End Learning and Planning
Figure 2 for The Predictron: End-To-End Learning and Planning
Figure 3 for The Predictron: End-To-End Learning and Planning
Figure 4 for The Predictron: End-To-End Learning and Planning
Viaarxiv icon

Deep Reinforcement Learning in Large Discrete Action Spaces

Apr 04, 2016
Gabriel Dulac-Arnold, Richard Evans, Hado van Hasselt, Peter Sunehag, Timothy Lillicrap, Jonathan Hunt, Timothy Mann, Theophane Weber, Thomas Degris, Ben Coppin

Figure 1 for Deep Reinforcement Learning in Large Discrete Action Spaces
Figure 2 for Deep Reinforcement Learning in Large Discrete Action Spaces
Figure 3 for Deep Reinforcement Learning in Large Discrete Action Spaces
Figure 4 for Deep Reinforcement Learning in Large Discrete Action Spaces
Viaarxiv icon