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2020 – today
- 2024
[c30]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- [c29]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. ICML 2024 - [i25]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 abs/2401.14953 (2024) - 2023
- [c28]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: 1889-1903 - [c27]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 - [c26]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: 11173-11195 - [c25]Elliot Catt, Jordi Grau-Moya, Marcus Hutter, Matthew Aitchison, Tim Genewein, Grégoire Delétang, Kevin Li, Joel Veness:
Self-Predictive Universal AI. NeurIPS 2023 - [i24]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 abs/2302.03067 (2023) - [i23]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 abs/2305.16843 (2023) - [i22]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 abs/2309.10668 (2023) - 2022
- [c24]Elliot Catt
, Marcus Hutter, Joel Veness:
Reinforcement Learning with Information-Theoretic Actuation. AGI 2022: 188-198 - [i21]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 abs/2209.15618 (2022) - 2021
- [c23]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: 10015-10023 - [i20]Elliot Catt, Marcus Hutter, Joel Veness:
Reinforcement Learning with Information-Theoretic Actuation. CoRR abs/2109.15147 (2021) - [i19]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 abs/2110.10819 (2021) - 2020
- [c22]David Budden, Adam H. Marblestone, Eren Sezener, Tor Lattimore, Gregory Wayne, Joel Veness:
Gaussian Gated Linear Networks. NeurIPS 2020 - [c21]Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness:
Online Learning in Contextual Bandits using Gated Linear Networks. NeurIPS 2020 - [c20]Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness:
A Combinatorial Perspective on Transfer Learning. NeurIPS 2020 - [i18]Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness:
Online Learning in Contextual Bandits using Gated Linear Networks. CoRR abs/2002.11611 (2020) - [i17]David Budden, Adam H. Marblestone, Eren Sezener, Tor Lattimore, Greg Wayne, Joel Veness:
Gaussian Gated Linear Networks. CoRR abs/2006.05964 (2020) - [i16]Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness:
A Combinatorial Perspective on Transfer Learning. CoRR abs/2010.12268 (2020)
2010 – 2019
- 2019
- [i15]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:
Meta-learning of Sequential Strategies. CoRR abs/1905.03030 (2019) - [i14]Joel Veness, Tor Lattimore, Avishkar Bhoopchand, David Budden, Christopher Mattern, Agnieszka Grabska-Barwinska, Peter Toth, Simon Schmitt, Marcus Hutter:
Gated Linear Networks. CoRR abs/1910.01526 (2019) - 2018
- [j4]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: 523-562 (2018) - [c19]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: 5573-5577 - 2017
- [i13]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 abs/1709.06009 (2017) - [i12]Joel Veness, Tor Lattimore, Avishkar Bhoopchand, Agnieszka Grabska-Barwinska, Christopher Mattern, Peter Toth:
Online Learning with Gated Linear Networks. CoRR abs/1712.01897 (2017) - 2016
- [c18]Kieran Milan, Joel Veness, James Kirkpatrick, Michael H. Bowling, Anna Koop, Demis Hassabis:
The Forget-me-not Process. NIPS 2016: 3702-3710 - [i11]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 abs/1612.00796 (2016) - 2015
- [j3]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): 529-533 (2015) - [c17]Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins:
Compress and Control. AAAI 2015: 3016-3023 - [c16]Joel Veness, Marcus Hutter, Laurent Orseau, Marc G. Bellemare:
Online Learning of k-CNF Boolean Functions. IJCAI 2015: 3865-3873 - [c15]Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling:
The Arcade Learning Environment: An Evaluation Platform for General Agents (Extended Abstract). IJCAI 2015: 4148-4152 - [e1]Michael Bowling, Marc G. Bellemare, Erik Talvitie, Joel Veness, Marlos C. Machado:
Learning for General Competency in Video Games, Papers from the 2015 AAAI Workshop, Austin, Texas, USA, January 26, 2015. AAAI Technical Report WS-15-10, AAAI Press 2015, ISBN 978-1-57735-721-6 [contents] - 2014
- [c14]Marc G. Bellemare, Joel Veness, Erik Talvitie:
Skip Context Tree Switching. ICML 2014: 1458-1466 - [i10]Joel Veness, Marcus Hutter:
Online Learning of k-CNF Boolean Functions. CoRR abs/1403.6863 (2014) - [i9]Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins:
Compress and Control. CoRR abs/1411.5326 (2014) - 2013
- [j2]Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling:
The Arcade Learning Environment: An Evaluation Platform for General Agents. J. Artif. Intell. Res. 47: 253-279 (2013) - [c13]Joel Veness, Martha White, Michael Bowling, András György:
Partition Tree Weighting. DCC 2013: 321-330 - [c12]Marc G. Bellemare, Joel Veness, Michael Bowling:
Bayesian Learning of Recursively Factored Environments. ICML (3) 2013: 1211-1219 - [c11]Marc Lanctot, Abdallah Saffidine, Joel Veness, Christopher Archibald, Mark H. M. Winands:
Monte Carlo *-Minimax Search. IJCAI 2013: 580-586 - [i8]Marc Lanctot, Abdallah Saffidine, Joel Veness, Christopher Archibald, Mark H. M. Winands:
Monte Carlo *-Minimax Search. CoRR abs/1304.6057 (2013) - 2012
- [c10]Marc G. Bellemare, Joel Veness, Michael Bowling:
Investigating Contingency Awareness Using Atari 2600 Games. AAAI 2012: 864-871 - [c9]Joel Veness, Peter Sunehag, Marcus Hutter:
On Ensemble Techniques for AIXI Approximation. AGI 2012: 341-351 - [c8]Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling:
Context Tree Switching. DCC 2012: 327-336 - [c7]Marc G. Bellemare, Joel Veness, Michael Bowling:
Sketch-Based Linear Value Function Approximation. NIPS 2012: 2222-2230 - [i7]Joel Veness, Marcus Hutter:
Sparse Sequential Dirichlet Coding. CoRR abs/1206.3618 (2012) - [i6]Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling:
The Arcade Learning Environment: An Evaluation Platform for General Agents. CoRR abs/1207.4708 (2012) - [i5]Joel Veness, Martha White, Michael Bowling, András György:
Partition Tree Weighting. CoRR abs/1211.0587 (2012) - 2011
- [b1]Joel Veness:
Approximate universal artificial intelligence and self-play learning for games. University of New South Wales, Sydney, Australia, 2011 - [j1]Joel Veness, Kee Siong Ng, Marcus Hutter, William T. B. Uther, David Silver:
A Monte-Carlo AIXI Approximation. J. Artif. Intell. Res. 40: 95-142 (2011) - [c6]Shane Legg, Joel Veness:
An Approximation of the Universal Intelligence Measure. Algorithmic Probability and Friends 2011: 236-249 - [c5]Joel Veness, Marc Lanctot, Michael H. Bowling:
Variance Reduction in Monte-Carlo Tree Search. NIPS 2011: 1836-1844 - [i4]Shane Legg, Joel Veness:
An Approximation of the Universal Intelligence Measure. CoRR abs/1109.5951 (2011) - [i3]Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling:
Context Tree Switching. CoRR abs/1111.3182 (2011) - 2010
- [c4]Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver:
Reinforcement Learning via AIXI Approximation. AAAI 2010: 605-611 - [c3]David Silver, Joel Veness:
Monte-Carlo Planning in Large POMDPs. NIPS 2010: 2164-2172 - [i2]Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver:
Reinforcement Learning via AIXI Approximation. CoRR abs/1007.2049 (2010)
2000 – 2009
- 2009
- [c2]Joel Veness, David Silver, William T. B. Uther, Alan Blair:
Bootstrapping from Game Tree Search. NIPS 2009: 1937-1945 - [i1]Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver:
A Monte Carlo AIXI Approximation. CoRR abs/0909.0801 (2009) - 2007
- [c1]Joel Veness, Alan Blair:
Effective Use of Transposition Tables in Stochastic Game Tree Search. CIG 2007: 112-116
Coauthor Index
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