Lillicrap, Timothy P.

14 publications

ICLR 2025 AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents Christopher Rawles, Sarah Clinckemaillie, Yifan Chang, Jonathan Waltz, Gabrielle Lau, Marybeth Fair, Alice Li, William E Bishop, Wei Li, Folawiyo Campbell-Ajala, Daniel Kenji Toyama, Robert James Berry, Divya Tyamagundlu, Timothy P Lillicrap, Oriana Riva

TMLR 2025 Exploring Exploration with Foundation Agents in Interactive Environments Daniel P. Sawyer, Nan Rosemary Ke, Hubert Soyer, Martin Engelcke, John Reid, David P Reichert, Drew A. Hudson, Alexander Lerchner, Danilo Jimenez Rezende, Timothy P Lillicrap, Michael Curtis Mozer, Jane X Wang

ICLRW 2025 Societal Alignment Frameworks Can Improve LLM Alignment Karolina Stanczak, Nicholas Meade, Mehar Bhatia, Hattie Zhou, Konstantin Böttinger, Jeremy Barnes, Jason Stanley, Jessica Montgomery, Richard Zemel, Nicolas Papernot, Nicolas Chapados, Denis Therien, Timothy P Lillicrap, Ana Marasovic, Sylvie Delacroix, Gillian K Hadfield, Siva Reddy

ICMLW 2024 Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving Aniket Rajiv Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P Lillicrap, Danilo Jimenez Rezende, Yoshua Bengio, Michael Curtis Mozer, Sanjeev Arora

NeurIPSW 2024 Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning Yuxi Xie, Anirudh Goyal, Wenyue Zheng, Min-Yen Kan, Timothy P Lillicrap, Kenji Kawaguchi, Michael Shieh

ICLR 2023 Evaluating Long-Term Memory in 3D Mazes Jurgis Pašukonis, Timothy P Lillicrap, Danijar Hafner

UAI 2022 Equilibrium Aggregation: Encoding Sets via Optimization Sergey Bartunov, Fabian B. Fuchs, Timothy P. Lillicrap

NeurIPSW 2022 Evaluating Long-Term Memory in 3D Mazes Jurgis Pašukonis, Timothy P Lillicrap, Danijar Hafner

ICLR 2021 Mastering Atari with Discrete World Models Danijar Hafner, Timothy P Lillicrap, Mohammad Norouzi, Jimmy Ba

ICLR 2020 Compressive Transformers for Long-Range Sequence Modelling Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, Timothy P. Lillicrap

ICLR 2020 Meta-Learning Deep Energy-Based Memory Models Sergey Bartunov, Jack W Rae, Simon Osindero, Timothy P Lillicrap

ICML 2017 Learning to Learn Without Gradient Descent by Gradient Descent Yutian Chen, Matthew W. Hoffman, Sergio Gómez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Matt Botvinick, Nando Freitas

ICLR 2017 Q-Prop: Sample-Efficient Policy Gradient with an Off-Policy Critic Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine

ICLR 2016 Continuous Control with Deep Reinforcement Learning Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, Daan Wierstra