John Quan

Researcher, Meta

Joined

December 2017

Names

John Quan

Emails

****@google.com (Confirmed)

****@deepmind.com (Confirmed)

****@yahoo.com (Confirmed)

****@meta.com (Confirmed)

Personal Links

Google Scholar

DBLP

Career & Education History

Researcher

Meta (meta.com)

2024 – Present

Researcher

DeepMind (deepmind.com)

2014 – 2024

Advisors, Relations & Conflicts

No relations added

Expertise

No areas of expertise listed

Publications

Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability
Shobhita Sundaram, John Quan, Ariel Kwiatkowski, Kartik Ahuja, Yann Ollivier, Julia Kempe
- ICLR 2026 Workshop RSI Poster
- Readers: Everyone
Large Language Models as Improvement Operators: Better Reasoning by Iteration
Lovish Madaan, Aniket Rajiv Didolkar, Suchin Gururangan, John Quan, Ruan Silva, Ruslan Salakhutdinov, Manzil Zaheer, Sanjeev Arora, Anirudh Goyal
- Submitted to ICLR 2026
- Readers: Everyone
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 et al. (4 additional authors not shown)
- ALOE 2023 Poster
- Readers: Everyone
The Phenomenon of Policy Churn
Tom Schaul, Andre Barreto, John Quan, Georg Ostrovski
- Published: 31 Oct 2022, Last Modified: 08 Feb 2026
- NeurIPS 2022 Accept
- Readers: Everyone
The value-improvement path: Towards better representations for reinforcement learning
Will Dabney, Andre Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G Bellemare, David Silver
- 11 May 2021
- OpenReview Archive Direct Upload
- Readers: Everyone
Deep Q-learning From Demonstrations
Todd Hester, Matej Vecerik, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Dan Horgan, John Quan, Andrew Sendonaris, Ian Osband, Gabriel Dulac-Arnold, John Agapiou, Joel Z. Leibo, Audrunas Gruslys
- 2018 (modified: 16 Jul 2019)
- AAAI 2018
- Readers: Everyone
Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement
André Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel J. Mankowitz, Augustin Zídek, Rémi Munos
- 2018 (modified: 11 Nov 2022)
- ICML 2018
- Readers: Everyone
Distral: Robust multitask reinforcement learning
Yee Whye Teh, Victor Bapst, Wojciech M. Czarnecki, John Quan, James Kirkpatrick, Raia Hadsell, Nicolas Heess, Razvan Pascanu
- 2017 (modified: 11 Nov 2022)
- NIPS 2017
- Readers: Everyone

Co-Authors

View all 67 co-authors