Quan, John

10 publications

NeurIPSW 2023 Vision-Language Models as a Source of Rewards Kate Baumli, Satinder Singh, Feryal Behbahani, Harris Chan, Gheorghe Comanici, Sebastian Flennerhag, Maxime Gazeau, Kristian Holsheimer, Dan Horgan, Michael Laskin, Clare Lyle, Volodymyr Mnih, Alexander Neitz, Fabio Pardo, Jack Parker-Holder, John Quan, Tim Rocktäschel, Himanshu Sahni, Tom Schaul, Yannick Schroecker, Stephen Spencer, Richie Steigerwald, Luyu Wang, Lei M Zhang

NeurIPS 2022 The Phenomenon of Policy Churn Tom Schaul, Andre Barreto, John Quan, Georg Ostrovski

AAAI 2021 The Value-Improvement Path: Towards Better Representations for Reinforcement Learning Will Dabney, André Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G. Bellemare, David Silver

ICLR 2019 Recurrent Experience Replay in Distributed Reinforcement Learning Steven Kapturowski, Georg Ostrovski, John Quan, Remi Munos, Will Dabney

ICLR 2019 Universal Successor Features Approximators Diana Borsa, Andre Barreto, John Quan, Daniel J. Mankowitz, Hado van Hasselt, Remi Munos, David Silver, Tom Schaul

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

ICLR 2018 Distributed Prioritized Experience Replay Dan Horgan, John Quan, David Budden, Gabriel Barth-Maron, Matteo Hessel, Hado van Hasselt, David Silver

ICML 2018 Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement Andre Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel Mankowitz, Augustin Zidek, Remi Munos

NeurIPS 2017 Distral: Robust Multitask Reinforcement Learning Yee Teh, Victor Bapst, Wojciech M. Czarnecki, John Quan, James Kirkpatrick, Raia Hadsell, Nicolas Heess, Razvan Pascanu

ICLR 2016 Prioritized Experience Replay Tom Schaul, John Quan, Ioannis Antonoglou, David Silver