Joel Veness

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 28

Top Venues

CoRR

NeurIPS

IJCAI

ICLR

University of New South Wales, Sydney, Australia (PHD)

Education History

University of New South Wales, Sydney, Australia

PHD

Publications

Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Grégoire Delétang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness
Learning Universal Predictors. CoRR (2024)
Grégoire Delétang, 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
Language Modeling Is Compression. ICLR (2024)
Elliot Catt, Jordi Grau-Moya, Marcus Hutter, Matthew Aitchison, Tim Genewein, Grégoire Delétang, Kevin Li, Joel Veness
Self-Predictive Universal AI. NeurIPS (2023)
Anian Ruoss, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Róbert Csordás, Mehdi Bennani, Shane Legg, Joel Veness
Randomized Positional Encodings Boost Length Generalization of Transformers. CoRR (2023)
Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
Memory-Based Meta-Learning on Non-Stationary Distributions. CoRR (2023)
Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Chris Cundy, Marcus Hutter, Shane Legg, Joel Veness, Pedro A. Ortega
Neural Networks and the Chomsky Hierarchy. ICLR (2023)
Grégoire Delétang, 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
Language Modeling Is Compression. CoRR (2023)
Anian Ruoss, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Róbert Csordás, Mehdi Bennani, Shane Legg, Joel Veness
Randomized Positional Encodings Boost Length Generalization of Transformers. ACL (2) (2023)
Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
Memory-Based Meta-Learning on Non-Stationary Distributions. ICML (2023)
Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Tim Genewein, Elliot Catt, Kevin Li, Anian Ruoss, Chris Cundy, Joel Veness, Jane X. Wang, Marcus Hutter, Christopher Summerfield, Shane Legg, Pedro A. Ortega
Beyond Bayes-optimality: meta-learning what you know you don't know. CoRR (2022)
Elliot Catt, Marcus Hutter, Joel Veness
Reinforcement Learning with Information-Theoretic Actuation. AGI (2022)
Joel Veness, Tor Lattimore, David Budden, Avishkar Bhoopchand, Christopher Mattern, Agnieszka Grabska-Barwinska, Eren Sezener, Jianan Wang, Peter Toth, Simon Schmitt, Marcus Hutter
Gated Linear Networks. AAAI (2021)
Pedro A. Ortega, Markus Kunesch, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Joel Veness, Jonas Buchli, Jonas Degrave, Bilal Piot, Julien Pérolat, Tom Everitt, Corentin Tallec, Emilio Parisotto, Tom Erez, Yutian Chen, Scott E. Reed, Marcus Hutter, Nando de Freitas, Shane Legg
Shaking the foundations: delusions in sequence models for interaction and control. CoRR (2021)
Elliot Catt, Marcus Hutter, Joel Veness
Reinforcement Learning with Information-Theoretic Actuation. CoRR (2021)
Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness
A Combinatorial Perspective on Transfer Learning. NeurIPS (2020)
Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness
Online Learning in Contextual Bandits using Gated Linear Networks. CoRR (2020)
Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness
Online Learning in Contextual Bandits using Gated Linear Networks. NeurIPS (2020)
Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness
A Combinatorial Perspective on Transfer Learning. CoRR (2020)
David Budden, Adam H. Marblestone, Eren Sezener, Tor Lattimore, Gregory Wayne, Joel Veness
Gaussian Gated Linear Networks. NeurIPS (2020)
David Budden, Adam H. Marblestone, Eren Sezener, Tor Lattimore, Greg Wayne, Joel Veness
Gaussian Gated Linear Networks. CoRR (2020)
Joel Veness, Tor Lattimore, Avishkar Bhoopchand, David Budden, Christopher Mattern, Agnieszka Grabska-Barwinska, Peter Toth, Simon Schmitt, Marcus Hutter
Gated Linear Networks. CoRR (2019)
Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alexander Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin J. Miller, Mohammad Gheshlaghi Azar, Ian Osband, Neil C. Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew Botvinick, Shane Legg
Meta-learning of Sequential Strategies. CoRR (2019)
Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. J. Artif. Intell. Res. 61 (2018)
Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (Extended Abstract). IJCAI (2018)
Joel Veness, Tor Lattimore, Avishkar Bhoopchand, Agnieszka Grabska-Barwinska, Christopher Mattern, Peter Toth
Online Learning with Gated Linear Networks. CoRR (2017)
Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. CoRR (2017)
Kieran Milan, Joel Veness, James Kirkpatrick, Michael H. Bowling, Anna Koop, Demis Hassabis
The Forget-me-not Process. NIPS (2016)
James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A. Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, Raia Hadsell
Overcoming catastrophic forgetting in neural networks. CoRR (2016)
Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling
The Arcade Learning Environment: An Evaluation Platform for General Agents (Extended Abstract). IJCAI (2015)
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin A. Riedmiller, Andreas Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, Demis Hassabis
Human-level control through deep reinforcement learning. Nat. 518 (7540) (2015)
Joel Veness, Marcus Hutter, Laurent Orseau, Marc G. Bellemare
Online Learning of k-CNF Boolean Functions. IJCAI (2015)
Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins
Compress and Control. AAAI (2015)
Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins
Compress and Control. CoRR (2014)
Marc G. Bellemare, Joel Veness, Erik Talvitie
Skip Context Tree Switching. ICML (2014)
Joel Veness, Marcus Hutter
Online Learning of k-CNF Boolean Functions. CoRR (2014)
Marc G. Bellemare, Joel Veness, Michael Bowling
Bayesian Learning of Recursively Factored Environments. ICML (3) (2013)
Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling
The Arcade Learning Environment: An Evaluation Platform for General Agents. J. Artif. Intell. Res. 47 (2013)
Joel Veness, Martha White, Michael Bowling, András György
Partition Tree Weighting. DCC (2013)
Marc Lanctot, Abdallah Saffidine, Joel Veness, Christopher Archibald, Mark H. M. Winands
Monte Carlo *-Minimax Search CoRR (2013)
Marc Lanctot, Abdallah Saffidine, Joel Veness, Christopher Archibald, Mark H. M. Winands
Monte Carlo *-Minimax Search. IJCAI (2013)
Marc G. Bellemare, Joel Veness, Michael Bowling
Investigating Contingency Awareness Using Atari 2600 Games. AAAI (2012)
Marc G. Bellemare, Joel Veness, Michael Bowling
Sketch-Based Linear Value Function Approximation. NIPS (2012)
Joel Veness, Marcus Hutter
Sparse Sequential Dirichlet Coding CoRR (2012)
Joel Veness, Martha White, Michael Bowling, András György
Partition Tree Weighting CoRR (2012)
Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling
Context Tree Switching. DCC (2012)
Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling
The Arcade Learning Environment: An Evaluation Platform for General Agents CoRR (2012)
Joel Veness, Peter Sunehag, Marcus Hutter
On Ensemble Techniques for AIXI Approximation. AGI (2012)
Joel Veness, Kee Siong Ng, Marcus Hutter, William T. B. Uther, David Silver
A Monte-Carlo AIXI Approximation. J. Artif. Intell. Res. 40 (2011)
Shane Legg, Joel Veness
An Approximation of the Universal Intelligence Measure CoRR (2011)
Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling
Context Tree Switching CoRR (2011)
Shane Legg, Joel Veness
An Approximation of the Universal Intelligence Measure. Algorithmic Probability and Friends (2011)
Joel Veness, Marc Lanctot, Michael H. Bowling
Variance Reduction in Monte-Carlo Tree Search. NIPS (2011)
Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
Reinforcement Learning via AIXI Approximation. AAAI (2010)
Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
Reinforcement Learning via AIXI Approximation CoRR (2010)
David Silver, Joel Veness
Monte-Carlo Planning in Large POMDPs. NIPS (2010)
Joel Veness, David Silver, William T. B. Uther, Alan Blair
Bootstrapping from Game Tree Search. NIPS (2009)
Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
A Monte Carlo AIXI Approximation CoRR (2009)
Joel Veness, Alan Blair
Effective Use of Transposition Tables in Stochastic Game Tree Search. CIG (2007)

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Publication Activity (10 Years)

Top Topics

Top Venues

Joel Veness