Timothy P. Lillicrap

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

Venues

Active years

2016–2025

Best venue rank

Where they publish

Papers

30 indexed papers, newest first.

Year	Venue	Title	Authors
2025	ICLR	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
2023	ICLR	Evaluating Long-Term Memory in 3D Mazes.	Jurgis Pasukonis, Timothy P. Lillicrap, Danijar Hafner
2022	ICML	Retrieval-Augmented Reinforcement Learning.	Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adri Puigdomnech Badia, Arthur Guez, Mehdi Mirza, Peter Conway Humphreys, Ksenia Konyushkova, Michal Valko, Simon Osindero, Timothy P. Lillicrap, Nicolas Heess, Charles Blundell
2022	ICML	A data-driven approach for learning to control computers.	Peter Conway Humphreys, David Raposo, Tobias Pohlen, Gregory Thornton, Rachita Chhaparia, Alistair Muldal, Josh Abramson, Petko Georgiev, Adam Santoro, Timothy P. Lillicrap
2022	UAI	Equilibrium aggregation: encoding sets via optimization.	Sergey Bartunov, Fabian B. Fuchs, Timothy P. Lillicrap
2021	ICLR	Mastering Atari with Discrete World Models.	Danijar Hafner, Timothy P. Lillicrap, Mohammad Norouzi, Jimmy Ba
2020	ICLR	Meta-Learning Deep Energy-Based Memory Models.	Sergey Bartunov, Jack W. Rae, Simon Osindero, Timothy P. Lillicrap
2020	ICLR	Dream to Control: Learning Behaviors by Latent Imagination.	Danijar Hafner, Timothy P. Lillicrap, Jimmy Ba, Mohammad Norouzi
2020	ICLR	Automated curriculum generation through setter-solver interactions.	Sbastien Racanire, Andrew K. Lampinen, Adam Santoro, David P. Reichert, Vlad Firoiu, Timothy P. Lillicrap
2020	ICLR	Compressive Transformers for Long-Range Sequence Modelling.	Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, Chloe Hillier, Timothy P. Lillicrap
2019	ICLR	Recall Traces: Backtracking Models for Efficient Reinforcement Learning.	Anirudh Goyal, Philemon Brakel, William Fedus, Soumye Singhal, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio
2019	ICLR	Learning to Make Analogies by Contrasting Abstract Relational Structure.	Felix Hill, Adam Santoro, David G. T. Barrett, Ari S. Morcos, Timothy P. Lillicrap
2019	ICLR	Episodic Curiosity through Reachability.	Nikolay Savinov, Anton Raichuk, Damien Vincent, Raphal Marinier, Marc Pollefeys, Timothy P. Lillicrap, Sylvain Gelly
2019	ICLR	Deep reinforcement learning with relational inductive biases.	Vincius Flores Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David P. Reichert, Timothy P. Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew M. Botvinick, Oriol Vinyals, Peter W. Battaglia
2019	ICML	An Investigation of Model-Free Planning.	Arthur Guez, Mehdi Mirza, Karol Gregor, Rishabh Kabra, Sbastien Racanire, Theophane Weber, David Raposo, Adam Santoro, Laurent Orseau, Tom Eccles, Greg Wayne, David Silver, Timothy P. Lillicrap
2019	ICML	Learning Latent Dynamics for Planning from Pixels.	Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson
2019	ICML	Composing Entropic Policies using Divergence Correction.	Jonathan J. Hunt, Andr Barreto, Timothy P. Lillicrap, Nicolas Heess
2019	ICML	Meta-Learning Neural Bloom Filters.	Jack W. Rae, Sergey Bartunov, Timothy P. Lillicrap
2019	ICML	Deep Compressed Sensing.	Yan Wu, Mihaela Rosca, Timothy P. Lillicrap
2019	UAI	Noise Contrastive Priors for Functional Uncertainty.	Danijar Hafner, Dustin Tran, Timothy P. Lillicrap, Alex Irpan, James Davidson
2018	ICLR	Distributed Distributional Deterministic Policy Gradients.	Gabriel Barth-Maron, Matthew W. Hoffman, David Budden, Will Dabney, Dan Horgan, Dhruva TB, Alistair Muldal, Nicolas Heess, Timothy P. Lillicrap
2018	ICLR	The Kanerva Machine: A Generative Distributed Memory.	Yan Wu, Greg Wayne, Alex Graves, Timothy P. Lillicrap
2018	ICML	Fast Parametric Learning with Activation Memorization.	Jack W. Rae, Chris Dyer, Peter Dayan, Timothy P. Lillicrap
2018	ICML	Measuring abstract reasoning in neural networks.	Adam Santoro, Felix Hill, David G. T. Barrett, Ari S. Morcos, Timothy P. Lillicrap
2017	ICLR	Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic.	Shixiang Gu, Timothy P. Lillicrap, Zoubin Ghahramani, Richard E. Turner, Sergey Levine
2017	ICML	Learning to Learn without Gradient Descent by Gradient Descent.	Yutian Chen, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Matthew M. Botvinick, Nando de Freitas
2017	ICRA	Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates.	Shixiang Gu, Ethan Holly, Timothy P. Lillicrap, Sergey Levine
2016	ICML	Continuous Deep Q-Learning with Model-based Acceleration.	Shixiang Gu, Timothy P. Lillicrap, Ilya Sutskever, Sergey Levine
2016	ICML	Asynchronous Methods for Deep Reinforcement Learning.	Volodymyr Mnih, Adri Puigdomnech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu
2016	ICML	Meta-Learning with Memory-Augmented Neural Networks.	Adam Santoro, Sergey Bartunov, Matthew M. Botvinick, Daan Wierstra, Timothy P. Lillicrap