Veness, Joel

28 publications

ICML 2025 Compression via Pre-Trained Transformers: A Study on Byte-Level Multimodal Data David Heurtel-Depeiges, Anian Ruoss, Joel Veness, Tim Genewein

NeurIPS 2024 Amortized Planning with Large-Scale Transformers: A Case Study on Chess Anian Ruoss, Grégoire Delétang, Sourabh Medapati, Jordi Grau-Moya, Li Kevin Wenliang, Elliot Catt, John Reid, Cannada A. Lewis, Joel Veness, Tim Genewein

ICLR 2024 Language Modeling Is Compression Gregoire Deletang, Anian Ruoss, Paul-Ambroise Duquenne, Elliot Catt, Tim Genewein, Christopher Mattern, Jordi Grau-Moya, Li Kevin Wenliang, Matthew Aitchison, Laurent Orseau, Marcus Hutter, Joel Veness

ICML 2024 Learning Universal Predictors Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Gregoire Deletang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness

ICML 2023 Memory-Based Meta-Learning on Non-Stationary Distributions Tim Genewein, Gregoire Deletang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness

ICLR 2023 Neural Networks and the Chomsky Hierarchy Gregoire Deletang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Chris Cundy, Marcus Hutter, Shane Legg, Joel Veness, Pedro A Ortega

NeurIPS 2023 Self-Predictive Universal AI Elliot Catt, Jordi Grau-Moya, Marcus Hutter, Matthew Aitchison, Tim Genewein, Grégoire Delétang, Kevin Li, Joel Veness

AAAI 2021 Gated Linear Networks Joel Veness, Tor Lattimore, David Budden, Avishkar Bhoopchand, Christopher Mattern, Agnieszka Grabska-Barwinska, Eren Sezener, Jianan Wang, Peter Toth, Simon Schmitt, Marcus Hutter

NeurIPS 2020 A Combinatorial Perspective on Transfer Learning Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness

NeurIPS 2020 Gaussian Gated Linear Networks David Budden, Adam Marblestone, Eren Sezener, Tor Lattimore, Gregory Wayne, Joel Veness

NeurIPS 2020 Online Learning in Contextual Bandits Using Gated Linear Networks Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness

JAIR 2018 Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling

IJCAI 2018 Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (Extended Abstract) Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling

NeurIPS 2016 The Forget-Me-Not Process Kieran Milan, Joel Veness, James Kirkpatrick, Michael Bowling, Anna Koop, Demis Hassabis

AAAI 2015 Compress and Control Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins

IJCAI 2015 Online Learning of K-CNF Boolean Functions Joel Veness, Marcus Hutter, Laurent Orseau, Marc G. Bellemare

IJCAI 2015 The Arcade Learning Environment: An Evaluation Platform for General Agents (Extended Abstract) Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling

ICML 2014 Skip Context Tree Switching Marc Bellemare, Joel Veness, Erik Talvitie

ICML 2013 Bayesian Learning of Recursively Factored Environments Marc Bellemare, Joel Veness, Michael Bowling

IJCAI 2013 Monte Carlo *-Minimax Search Marc Lanctot, Abdallah Saffidine, Joel Veness, Christopher Archibald, Mark H. M. Winands

JAIR 2013 The Arcade Learning Environment: An Evaluation Platform for General Agents Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling

AAAI 2012 Investigating Contingency Awareness Using Atari 2600 Games Marc G. Bellemare, Joel Veness, Michael Bowling

NeurIPS 2012 Sketch-Based Linear Value Function Approximation Marc Bellemare, Joel Veness, Michael Bowling

JAIR 2011 A Monte-Carlo AIXI Approximation Joel Veness, Kee Siong Ng, Marcus Hutter, William T. B. Uther, David Silver

NeurIPS 2011 Variance Reduction in Monte-Carlo Tree Search Joel Veness, Marc Lanctot, Michael Bowling

NeurIPS 2010 Monte-Carlo Planning in Large POMDPs David Silver, Joel Veness

AAAI 2010 Reinforcement Learning via AIXI Approximation Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver

NeurIPS 2009 Bootstrapping from Game Tree Search Joel Veness, David Silver, Alan Blair, William Uther