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ORCIDLi Kevin Wenliang
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- affiliation: University College London, Gatsby Unit, UK
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2020 – today
- 2024
[c9]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- [c8]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 - [c7]Li Kevin Wenliang, Grégoire Delétang, Matthew Aitchison, Marcus Hutter, Anian Ruoss, Arthur Gretton, Mark Rowland:
Distributional Bellman Operators over Mean Embeddings. ICML 2024 - [i13]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) - [i12]Anian Ruoss, Grégoire Delétang, Sourabh Medapati, Jordi Grau-Moya, Li Kevin Wenliang, Elliot Catt, John Reid, Tim Genewein:
Grandmaster-Level Chess Without Search. CoRR abs/2402.04494 (2024) - [i11]Mark Rowland, Li Kevin Wenliang, Rémi Munos, Clare Lyle, Yunhao Tang, Will Dabney:
Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model. CoRR abs/2402.07598 (2024) - 2023
- [c6]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 - [c5]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 - [i10]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) - [i9]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) - [i8]Zhe Wang, Petar Velickovic, Daniel Hennes, Nenad Tomasev, Laurel Prince, Michael Kaisers, Yoram Bachrach, Romuald Elie, Li Kevin Wenliang, Federico Piccinini, William Spearman, Ian Graham, Jerome T. Connor, Yi Yang, Adrià Recasens, Mina Khan, Nathalie Beauguerlange, Pablo Sprechmann, Pol Moreno, Nicolas Heess, Michael Bowling, Demis Hassabis, Karl Tuyls:
TacticAI: an AI assistant for football tactics. CoRR abs/2310.10553 (2023) - [i7]Li Kevin Wenliang, Ben Moran:
Score-based generative models learn manifold-like structures with constrained mixing. CoRR abs/2311.09952 (2023) - [i6]Li Kevin Wenliang, Grégoire Delétang, Matthew Aitchison, Marcus Hutter, Anian Ruoss, Arthur Gretton, Mark Rowland:
Distributional Bellman Operators over Mean Embeddings. CoRR abs/2312.07358 (2023) - 2022
- [i5]Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Marcus Hutter, Shane Legg, Pedro A. Ortega:
Neural Networks and the Chomsky Hierarchy. CoRR abs/2207.02098 (2022) - [i4]Li Kevin Wenliang:
On the failure of variational score matching for VAE models. CoRR abs/2210.13390 (2022) - 2021
- [b1]Li Kevin Wenliang:
Nonparametric enrichment in computational and biological representations of distributions. University College London, UK, 2021 - [c4]Longyuan Li, Jian Yao, Li K. Wenliang, Tong He, Tianjun Xiao, Junchi Yan, David Wipf, Zheng Zhang:
GRIN: Generative Relation and Intention Network for Multi-agent Trajectory Prediction. NeurIPS 2021: 27107-27118 - 2020
- [c3]Li K. Wenliang, Theodore H. Moskovitz, Heishiro Kanagawa, Maneesh Sahani:
Amortised Learning by Wake-Sleep. ICML 2020: 10236-10247 - [c2]Tianlin Xu, Li Kevin Wenliang, Michael Munn, Beatrice Acciaio:
COT-GAN: Generating Sequential Data via Causal Optimal Transport. NeurIPS 2020 - [i3]Li Kevin Wenliang, Theodore H. Moskovitz, Heishiro Kanagawa, Maneesh Sahani:
Amortised Learning by Wake-Sleep. CoRR abs/2002.09737 (2020) - [i2]Tianlin Xu, Li Kevin Wenliang, Michael Munn, Beatrice Acciaio:
COT-GAN: Generating Sequential Data via Causal Optimal Transport. CoRR abs/2006.08571 (2020) - [i1]Li K. Wenliang:
Blindness of score-based methods to isolated components and mixing proportions. CoRR abs/2008.10087 (2020)
2010 – 2019
- 2019
- [c1]Li Kevin Wenliang, Maneesh Sahani:
A neurally plausible model for online recognition and postdiction in a dynamical environment. NeurIPS 2019: 9641-9652
Coauthor Index
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