Joel Veness - RankMe

65 papers A* 19B 2Journal 31Unranked 11

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data. ICML David Heurtel-Depeiges, Anian Ruoss, Joel Veness, Tim Genewein
2025	J	`jnl`	Partition Tree Weighting for Non-Stationary Stochastic Bandits. CoRR Joel Veness, Marcus Hutter, András György, Jordi Grau-Moya
2024	A*	`conf`	Amortized Planning with Large-Scale Transformers: A Case Study on Chess. NeurIPS Anian Ruoss, Grégoire Delétang, Sourabh Medapati, Jordi Grau-Moya, Kevin Li, Elliot Catt, John Reid, Cannada A. Lewis, Joel Veness, Tim Genewein
2024	J	`jnl`	Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data. CoRR David Heurtel-Depeiges, Anian Ruoss, Joel Veness, Tim Genewein
2024	A*	`conf`	Language Modeling Is Compression. ICLR 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
2024	A*	`conf`	Learning Universal Predictors. ICML Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Grégoire Delétang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness
2024	J	`jnl`	Learning Universal Predictors. CoRR Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Grégoire Delétang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness
2023	J	`jnl`	Language Modeling Is Compression. CoRR 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
2023	A*	`conf`	Memory-Based Meta-Learning on Non-Stationary Distributions. ICML Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
2023	J	`jnl`	Memory-Based Meta-Learning on Non-Stationary Distributions. CoRR Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
2023	A*	`conf`	Neural Networks and the Chomsky Hierarchy. ICLR 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
2023	—	`conf`	Randomized Positional Encodings Boost Length Generalization of Transformers. ACL (2) Anian Ruoss, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Róbert Csordás, Mehdi Bennani, Shane Legg, Joel Veness
2023	J	`jnl`	Randomized Positional Encodings Boost Length Generalization of Transformers. CoRR Anian Ruoss, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Róbert Csordás, Mehdi Bennani, Shane Legg, Joel Veness
2023	A*	`conf`	Self-Predictive Universal AI. NeurIPS Elliot Catt, Jordi Grau-Moya, Marcus Hutter, Matthew Aitchison, Tim Genewein, Grégoire Delétang, Kevin Li, Joel Veness
2022	J	`jnl`	Beyond Bayes-optimality: meta-learning what you know you don't know. CoRR 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
2022	—	`conf`	Reinforcement Learning with Information-Theoretic Actuation. AGI Elliot Catt, Marcus Hutter, Joel Veness
2021	A*	`conf`	Gated Linear Networks. AAAI Joel Veness, Tor Lattimore, David Budden, Avishkar Bhoopchand, Christopher Mattern, Agnieszka Grabska-Barwinska, Eren Sezener, Jianan Wang, Peter Toth, Simon Schmitt, Marcus Hutter
2021	J	`jnl`	Reinforcement Learning with Information-Theoretic Actuation. CoRR Elliot Catt, Marcus Hutter, Joel Veness
2021	J	`jnl`	Shaking the foundations: delusions in sequence models for interaction and control. CoRR 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
2020	A*	`conf`	A Combinatorial Perspective on Transfer Learning. NeurIPS Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness
2020	J	`jnl`	A Combinatorial Perspective on Transfer Learning. CoRR Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness
2020	A*	`conf`	Gaussian Gated Linear Networks. NeurIPS David Budden, Adam H. Marblestone, Eren Sezener, Tor Lattimore, Gregory Wayne, Joel Veness
2020	J	`jnl`	Gaussian Gated Linear Networks. CoRR David Budden, Adam H. Marblestone, Eren Sezener, Tor Lattimore, Greg Wayne, Joel Veness
2020	A*	`conf`	Online Learning in Contextual Bandits using Gated Linear Networks. NeurIPS Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness
2020	J	`jnl`	Online Learning in Contextual Bandits using Gated Linear Networks. CoRR Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness
2019	J	`jnl`	Gated Linear Networks. CoRR Joel Veness, Tor Lattimore, Avishkar Bhoopchand, David Budden, Christopher Mattern, Agnieszka Grabska-Barwinska, Peter Toth, Simon Schmitt, Marcus Hutter
2019	J	`jnl`	Meta-learning of Sequential Strategies. CoRR 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 M. Botvinick, Shane Legg
2018	A*	`conf`	Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (Extended Abstract). IJCAI Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
2018	J	`jnl`	Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. J. Artif. Intell. Res. Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
2017	J	`jnl`	Online Learning with Gated Linear Networks. CoRR Joel Veness, Tor Lattimore, Avishkar Bhoopchand, Agnieszka Grabska-Barwinska, Christopher Mattern, Peter Toth
2017	J	`jnl`	Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. CoRR Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
2016	J	`jnl`	Overcoming catastrophic forgetting in neural networks. CoRR 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
2016	—	`conf`	The Forget-me-not Process. NIPS Kieran Milan, Joel Veness, James Kirkpatrick, Michael H. Bowling, Anna Koop, Demis Hassabis
2015	A*	`conf`	Compress and Control. AAAI Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins
2015	J	`jnl`	Human-level control through deep reinforcement learning. Nat. 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
2015	—	`ed.`	Learning for General Competency in Video Games, Papers from the 2015 AAAI Workshop, Austin, Texas, USA, January 26, 2015. AAAI Workshop: Learning for General Competency in Video Games Michael Bowling, Marc G. Bellemare, Erik Talvitie, Joel Veness, Marlos C. Machado
2015	A*	`conf`	Online Learning of k-CNF Boolean Functions. IJCAI Joel Veness, Marcus Hutter, Laurent Orseau, Marc G. Bellemare
2015	A*	`conf`	The Arcade Learning Environment: An Evaluation Platform for General Agents (Extended Abstract). IJCAI Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling
2014	J	`jnl`	Compress and Control. CoRR Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins
2014	J	`jnl`	Online Learning of k-CNF Boolean Functions. CoRR Joel Veness, Marcus Hutter
2014	A*	`conf`	Skip Context Tree Switching. ICML Marc G. Bellemare, Joel Veness, Erik Talvitie
2013	—	`conf`	Bayesian Learning of Recursively Factored Environments. ICML (3) Marc G. Bellemare, Joel Veness, Michael Bowling
2013	J	`jnl`	Monte Carlo *-Minimax Search CoRR Marc Lanctot, Abdallah Saffidine, Joel Veness, Christopher Archibald, Mark H. M. Winands
2013	A*	`conf`	Monte Carlo *-Minimax Search. IJCAI Marc Lanctot, Abdallah Saffidine, Joel Veness, Christopher Archibald, Mark H. M. Winands
2013	B	`conf`	Partition Tree Weighting. DCC Joel Veness, Martha White, Michael Bowling, András György
2013	J	`jnl`	The Arcade Learning Environment: An Evaluation Platform for General Agents. J. Artif. Intell. Res. Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling
2012	B	`conf`	Context Tree Switching. DCC Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling
2012	A*	`conf`	Investigating Contingency Awareness Using Atari 2600 Games. AAAI Marc G. Bellemare, Joel Veness, Michael Bowling
2012	—	`conf`	On Ensemble Techniques for AIXI Approximation. AGI Joel Veness, Peter Sunehag, Marcus Hutter
2012	J	`jnl`	Partition Tree Weighting CoRR Joel Veness, Martha White, Michael Bowling, András György
2012	—	`conf`	Sketch-Based Linear Value Function Approximation. NIPS Marc G. Bellemare, Joel Veness, Michael Bowling
2012	J	`jnl`	Sparse Sequential Dirichlet Coding CoRR Joel Veness, Marcus Hutter
2012	J	`jnl`	The Arcade Learning Environment: An Evaluation Platform for General Agents CoRR Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling
2011	J	`jnl`	A Monte-Carlo AIXI Approximation. J. Artif. Intell. Res. Joel Veness, Kee Siong Ng, Marcus Hutter, William T. B. Uther, David Silver
2011	J	`jnl`	An Approximation of the Universal Intelligence Measure CoRR Shane Legg, Joel Veness
2011	—	`conf`	An Approximation of the Universal Intelligence Measure. Algorithmic Probability and Friends Shane Legg, Joel Veness
2011	—	`—`	Approximate universal artificial intelligence and self-play learning for games. Joel Veness
2011	J	`jnl`	Context Tree Switching CoRR Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling
2011	—	`conf`	Variance Reduction in Monte-Carlo Tree Search. NIPS Joel Veness, Marc Lanctot, Michael H. Bowling
2010	—	`conf`	Monte-Carlo Planning in Large POMDPs. NIPS David Silver, Joel Veness
2010	J	`jnl`	Reinforcement Learning via AIXI Approximation CoRR Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
2010	A*	`conf`	Reinforcement Learning via AIXI Approximation. AAAI Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
2009	J	`jnl`	A Monte Carlo AIXI Approximation CoRR Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
2009	—	`conf`	Bootstrapping from Game Tree Search. NIPS Joel Veness, David Silver, William T. B. Uther, Alan Blair
2007	—	`conf`	Effective Use of Transposition Tables in Stochastic Game Tree Search. CIG Joel Veness, Alan Blair