Timothy Lillicrap
Impact in
- Artificial Intelligence top 0.02%
- Reinforcement Learning in Robotics
- Artificial Intelligence in Games
- Evolutionary Algorithms and Applications
- Adversarial Robustness in Machine Learning
- Neural Networks and Applications
- Health Informatics top 0.5%
Papers in
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- Neural dynamics and brain function 13
- EEG and Brain-Computer Interfaces 11
- Motor Control and Adaptation 8
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- Reinforcement Learning in Robotics 11
- Neural Networks and Applications 7
- Artificial Intelligence in Games 6
- Co-authors
- Demis Hassabis (4 shared papers)Thore Graepel (3 shared papers)Julian Schrittwieser (3 shared papers)Arthur Guez (3 shared papers)Ioannis Antonoglou (3 shared papers)David Lawrence Silver (3 shared papers)Laurent Sifre (3 shared papers)George van den Driessche (2 shared papers)
- Journals
- Nature (5 papers)Journal of Neurophysiology (4 papers)Nature Communications (3 papers)Behavioral and Brain Sciences (2 papers)Current Opinion in Neurobiology (2 papers)
- Partner nations
- United KingdomCanadaUnited States
In The Last Decade
Timothy Lillicrap
46 papers receiving 25.6k citations
Timothy Lillicrap's Hit Papers
Peers
Comparison fields: 5 of 221
- Artificial Intelligence 13.7k
- Health Informatics 291
- Computer Vision and Pattern Recognition 3.9k
- Cognitive Neuroscience 3.0k
- Control and Systems Engineering 2.9k
Countries citing papers authored by Timothy Lillicrap
This map shows the geographic impact of Timothy Lillicrap's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Timothy Lillicrap with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Timothy Lillicrap more than expected).
Fields of papers citing papers by Timothy Lillicrap
This network shows the impact of papers produced by Timothy Lillicrap. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Timothy Lillicrap. The network helps show where Timothy Lillicrap may publish in the future.
Co-authors
The 25 scholars most cited alongside Timothy Lillicrap, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Mastering the game of Go with deep neural networks and tree search Hit paper breakdown → | 2016 | 10419 |
| 2 | Mastering the game of Go without human knowledge Hit paper breakdown → | 2017 | 5979 |
| 3 | A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play Hit paper breakdown → | 2018 | 2231 |
| 4 | Grandmaster level in StarCraft II using multi-agent reinforcement learning Hit paper breakdown → | 2019 | 2212 |
| 5 | Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates Hit paper breakdown → | 2017 | 993 |
| 6 | Meta-learning with memory-augmented neural networks Hit paper breakdown → | 2016 | 782 |
| 7 | A deep learning framework for neuroscience Hit paper breakdown → | 2019 | 587 |
| 8 | Why Copy Others? Insights from the Social Learning Strategies Tournament Hit paper breakdown → | 2010 | 575 |
| 9 | Backpropagation and the brain Hit paper breakdown → | 2020 | 499 |
| 10 | Random synaptic feedback weights support error backpropagation for deep learning Hit paper breakdown → | 2016 | 435 |
| 11 | Vector-based navigation using grid-like representations in artificial agents Hit paper breakdown → | 2018 | 402 |
| 12 | 2017 | 222 | |
| 13 | Catalyzing next-generation Artificial Intelligence through NeuroAI Hit paper breakdown → | 2023 | 171 |
| 14 | 2009 | 118 | |
| 15 | 2020 | 108 | |
| 16 | 2013 | 96 | |
| 17 | 2018 | 83 | |
| 18 | 2017 | 82 | |
| 19 | 2019 | 74 | |
| 20 | Deep reinforcement learning with relational inductive biases | 2018 | 68 |
About Timothy Lillicrap
Timothy Lillicrap is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Electrical and Electronic Engineering, Biomedical Engineering and Cellular and Molecular Neuroscience, having authored 48 papers that have together received 26.5k indexed citations. Recurring topics across this work include Neural dynamics and brain function (13 papers), EEG and Brain-Computer Interfaces (11 papers), Reinforcement Learning in Robotics (11 papers), Advanced Memory and Neural Computing (10 papers), Motor Control and Adaptation (8 papers), Neural Networks and Applications (7 papers), Muscle activation and electromyography studies (7 papers) and Artificial Intelligence in Games (6 papers). The work is most often cited by research in Artificial Intelligence (13.7k citations), Health Informatics (291 citations), Computer Vision and Pattern Recognition (3.9k citations), Cognitive Neuroscience (3.0k citations) and Control and Systems Engineering (2.9k citations). Timothy Lillicrap has collaborated with scholars based in United Kingdom, Canada and United States. Frequent co-authors include Demis Hassabis, Thore Graepel, Julian Schrittwieser, Arthur Guez, Ioannis Antonoglou, David Lawrence Silver, Laurent Sifre, George van den Driessche, Aja Huang and Marc Lanctot. Their work appears in journals such as Nature, Journal of Neurophysiology, Nature Communications, Behavioral and Brain Sciences and Current Opinion in Neurobiology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.