Timothy P. Lillicrap

Affiliations:

Google DeepMind, London, UK
Queen's University, Kingston, Centre for Neuroscience Studies

According to our database¹, Timothy P. Lillicrap authored at least 98 papers between 2008 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Gemini: A Family of Highly Capable Multimodal Models.

[BibT_eX]

[DOI]

CoRR, 2023

Android in the Wild: A Large-Scale Dataset for Android Device Control.

[BibT_eX]

[DOI]

CoRR, 2023

Mastering Diverse Domains through World Models.

[BibT_eX]

[DOI]

CoRR, 2023

AndroidInTheWild: A Large-Scale Dataset For Android Device Control.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Evaluating Long-Term Memory in 3D Mazes.

[BibT_eX]

[DOI]

Jurgis Pasukonis

Timothy P. Lillicrap

Danijar Hafner

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

The Brain-Computer Metaphor Debate Is Useless: A Matter of Semantics.

[BibT_eX]

[DOI]

Blake A. Richards

Timothy P. Lillicrap

Frontiers Comput. Sci., 2022

Improving Multimodal Interactive Agents with Reinforcement Learning from Human Feedback.

[BibT_eX]

[DOI]

CoRR, 2022

Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution.

[BibT_eX]

[DOI]

CoRR, 2022

Evaluating Multimodal Interactive Agents.

[BibT_eX]

[DOI]

CoRR, 2022

Retrieval-Augmented Reinforcement Learning.

[BibT_eX]

[DOI]

Adrià Puigdomènech Badia

CoRR, 2022

A data-driven approach for learning to control computers.

[BibT_eX]

[DOI]

CoRR, 2022

Equilibrium aggregation: encoding sets via optimization.

[BibT_eX]

[DOI]

Sergey Bartunov

Fabian B. Fuchs

Timothy P. Lillicrap

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Intra-agent speech permits zero-shot task acquisition.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Large-Scale Retrieval for Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the Stability and Scalability of Node Perturbation Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A data-driven approach for learning to control computers.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Retrieval-Augmented Reinforcement Learning.

[BibT_eX]

[DOI]

Adrià Puigdomènech Badia

Proceedings of the International Conference on Machine Learning, 2022

2021

Creating Multimodal Interactive Agents with Imitation and Self-Supervised Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Symbolic Behaviour in Artificial Intelligence.

[BibT_eX]

[DOI]

CoRR, 2021

Towards Biologically Plausible Convolutional Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Mastering Atari with Discrete World Models.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

dm_control: Software and tasks for continuous control.

[BibT_eX]

[DOI]

Saran Tunyasuvunakool

Softw. Impacts, 2020

Mastering Atari, Go, chess and shogi by planning with a learned model.

[BibT_eX]

[DOI]

Nat., 2020

Imitating Interactive Intelligence.

[BibT_eX]

[DOI]

CoRR, 2020

Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban.

[BibT_eX]

[DOI]

CoRR, 2020

Physically Embedded Planning Problems: New Challenges for Reinforcement Learning.

[BibT_eX]

[DOI]

Saran Tunyasuvunakool

CoRR, 2020

Training Generative Adversarial Networks by Solving Ordinary Differential Equations.

[BibT_eX]

[DOI]

Chongli Qin

Yan Wu

Jost Tobias Springenberg

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Compressive Transformers for Long-Range Sequence Modelling.

[BibT_eX]

[DOI]

Jack W. Rae

Anna Potapenko

Siddhant M. Jayakumar

Chloe Hillier

Timothy P. Lillicrap

Proceedings of the 8th International Conference on Learning Representations, 2020

Automated curriculum generation through setter-solver interactions.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Dream to Control: Learning Behaviors by Latent Imagination.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Meta-Learning Deep Energy-Based Memory Models.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Grandmaster level in StarCraft II using multi-agent reinforcement learning.

[BibT_eX]

[DOI]

Nat., 2019

LOGAN: Latent Optimisation for Generative Adversarial Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Compressive Transformers for Long-Range Sequence Modelling.

[BibT_eX]

[DOI]

Jack W. Rae

Anna Potapenko

Siddhant M. Jayakumar

Timothy P. Lillicrap

CoRR, 2019

Automated curricula through setter-solver interactions.

[BibT_eX]

[DOI]

CoRR, 2019

What does it mean to understand a neural network?

[BibT_eX]

[DOI]

Timothy P. Lillicrap

Konrad P. Körding

CoRR, 2019

Is coding a relevant metaphor for building AI? A commentary on "Is coding a relevant metaphor for the brain?", by Romain Brette.

[BibT_eX]

[DOI]

CoRR, 2019

Noise Contrastive Priors for Functional Uncertainty.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Experience Replay for Continual Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Deep Learning without Weight Transport.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Deep Compressed Sensing.

[BibT_eX]

[DOI]

Yan Wu

Mihaela Rosca

Timothy P. Lillicrap

Proceedings of the 36th International Conference on Machine Learning, 2019

Meta-Learning Neural Bloom Filters.

[BibT_eX]

[DOI]

Jack W. Rae

Sergey Bartunov

Timothy P. Lillicrap

Proceedings of the 36th International Conference on Machine Learning, 2019

Composing Entropic Policies using Divergence Correction.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Learning Latent Dynamics for Planning from Pixels.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

An Investigation of Model-Free Planning.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Deep reinforcement learning with relational inductive biases.

[BibT_eX]

[DOI]

Vinícius Flores Zambaldi

Proceedings of the 7th International Conference on Learning Representations, 2019

Episodic Curiosity through Reachability.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Learning to Make Analogies by Contrasting Abstract Relational Structure.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Recall Traces: Backtracking Models for Efficient Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Vector-based navigation using grid-like representations in artificial agents.

[BibT_eX]

[DOI]

Nat., 2018

Entropic Policy Composition with Generalized Policy Improvement and Divergence Correction.

[BibT_eX]

[DOI]

CoRR, 2018

Optimizing Agent Behavior over Long Time Scales by Transporting Value.

[BibT_eX]

[DOI]

CoRR, 2018

Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors.

[BibT_eX]

[DOI]

CoRR, 2018

Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures.

[BibT_eX]

[DOI]

CoRR, 2018

Relational Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Vinícius Flores Zambaldi

CoRR, 2018

Recall Traces: Backtracking Models for Efficient Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2018

Unsupervised Predictive Memory in a Goal-Directed Agent.

[BibT_eX]

[DOI]

CoRR, 2018

DeepMind Control Suite.

[BibT_eX]

[DOI]

CoRR, 2018

Learning Attractor Dynamics for Generative Memory.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Relational recurrent neural networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Measuring abstract reasoning in neural networks.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Fast Parametric Learning with Activation Memorization.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

The Kanerva Machine: A Generative Distributed Memory.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Distributed Distributional Deterministic Policy Gradients.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Deep Learning with Dynamic Spiking Neurons and Fixed Feedback Weights.

[BibT_eX]

[DOI]

Arash Samadi

Timothy P. Lillicrap

Douglas B. Tweed

Neural Comput., 2017

Mastering the game of Go without human knowledge.

[BibT_eX]

[DOI]

George van den Driessche

Thore Graepel

Demis Hassabis

Nat., 2017

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm.

[BibT_eX]

[DOI]

CoRR, 2017

Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017.

[BibT_eX]

[DOI]

Danilo Jimenez Rezende

Adam Santoro

Tom Schaul

Christopher Summerfield

CoRR, 2017

StarCraft II: A New Challenge for Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2017

Data-efficient Deep Reinforcement Learning for Dexterous Manipulation.

[BibT_eX]

[DOI]

CoRR, 2017

Generative Temporal Models with Memory.

[BibT_eX]

[DOI]

Danilo Jimenez Rezende

David Amos

Timothy P. Lillicrap

CoRR, 2017

A simple neural network module for relational reasoning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Learning to Learn without Gradient Descent by Gradient Descent.

[BibT_eX]

[DOI]

Yutian Chen

Matthew W. Hoffman

Sergio Gomez Colmenarejo

Proceedings of the 34th International Conference on Machine Learning, 2017

Discovering objects and their relations from entangled scene representations.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Mastering the game of Go with deep neural networks and tree search.

[BibT_eX]

[DOI]

Nat., 2016

One-shot Learning with Memory-Augmented Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2016

Continuous control with deep reinforcement learning.

[BibT_eX]

[DOI]

Proceedings of the 4th International Conference on Learning Representations, 2016

Learning and Transfer of Modulated Locomotor Controllers.

[BibT_eX]

[DOI]

CoRR, 2016

Deep Reinforcement Learning for Robotic Manipulation.

[BibT_eX]

[DOI]

CoRR, 2016

Learning to Learn for Global Optimization of Black Box Functions.

[BibT_eX]

[DOI]

Yutian Chen

Matthew W. Hoffman

Sergio Gomez Colmenarejo

Misha Denil

Timothy P. Lillicrap

Nando de Freitas

CoRR, 2016

Matching Networks for One Shot Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Meta-Learning with Memory-Augmented Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

Asynchronous Methods for Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Volodymyr Mnih

Adrià Puigdomènech Badia

Proceedings of the 33nd International Conference on Machine Learning, 2016

Continuous Deep Q-Learning with Model-based Acceleration.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Towards Principled Unsupervised Learning.

[BibT_eX]

[DOI]

Ilya Sutskever

Rafal Józefowicz

Karol Gregor

Danilo Jimenez Rezende

Timothy P. Lillicrap

Oriol Vinyals

CoRR, 2015

Memory-based control with recurrent neural networks.

[BibT_eX]

[DOI]

CoRR, 2015

Learning Continuous Control Policies by Stochastic Value Gradients.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Random feedback weights support learning in deep neural networks.

[BibT_eX]

[DOI]

CoRR, 2014

2012

Relevance Realization and the Emerging Framework in Cognitive Science.

[BibT_eX]

[DOI]

John Vervaeke

Timothy P. Lillicrap

Blake A. Richards

J. Log. Comput., 2012

2008

Sensitivity Derivatives for Flexible Sensorimotor Learning.

[BibT_eX]

[DOI]

M. N. Abdelghani

Timothy P. Lillicrap

Douglas B. Tweed

Neural Comput., 2008

Timothy P. Lillicrap

Timeline

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