Clare Lyle
Impact in
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- Reinforcement Learning in Robotics
- Adversarial Robustness in Machine Learning
- Evolutionary Algorithms and Applications
- Anomaly Detection Techniques and Applications
- Machine Learning and Algorithms
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- Adaptive Dynamic Programming Control
Papers in
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- Reinforcement Learning in Robotics 2
- Domain Adaptation and Few-Shot Learning 2
- Data Stream Mining Techniques 1
- Evolutionary Algorithms and Applications 1
- Neural Networks and Applications 1
- Co-authors
- Marc G. Bellemare (2 shared papers)Pablo Samuel Castro (2 shared papers)Yarin Gal (5 shared papers)Shagun Sodhani (1 shared paper)Doina Precup (1 shared paper)Dale Schuurmans (1 shared paper)Mark van der Wilk (2 shared papers)Tor Lattimore (1 shared paper)
- Journals
- Nature (1 paper)International Conference on Learning Representations (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)Neural Information Processing Systems (3 papers)
- Partner nations
- United KingdomCanadaUnited States
In The Last Decade
Clare Lyle
7 papers receiving 28 citations
Peers
Comparison fields: 5 of 19
- Artificial Intelligence 24
- Computational Theory and Mathematics 4
- Computer Vision and Pattern Recognition 5
- Statistical and Nonlinear Physics 3
- Management Information Systems 2
Countries citing papers authored by Clare Lyle
This map shows the geographic impact of Clare Lyle'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 Clare Lyle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Clare Lyle more than expected).
Fields of papers citing papers by Clare Lyle
This network shows the impact of papers produced by Clare Lyle. 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 Clare Lyle. The network helps show where Clare Lyle may publish in the future.
Co-authors
The 18 scholars most cited alongside Clare Lyle, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 13 | |
| 2 | A Geometric Perspective on Optimal Representations for Reinforcement Learning | 2019 | 8 |
| 3 | Invariant Causal Prediction for Block MDPs | 2020 | 4 |
| 4 | A Bayesian Perspective on Training Speed and Model Selection | 2020 | 3 |
| 5 | Speedy Performance Estimation for Neural Architecture Search | 2021 | 2 |
| 6 | Resolving Causal Confusion in Reinforcement Learning via Robust Exploration | 2021 | 1 |
| 7 | Unpacking Information Bottlenecks: Surrogate Objectives for Deep Learning | 2021 | 1 |
| 8 | 2024 | 0 | |
| 9 | 2021 | 0 |
About Clare Lyle
Clare Lyle is a scholar working on Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition, Cognitive Neuroscience and Computational Theory and Mathematics, having authored 9 papers that have together received 32 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Behavioral and Psychological Studies (1 paper), Insect and Pesticide Research (1 paper), Data Stream Mining Techniques (1 paper), EEG and Brain-Computer Interfaces (1 paper), Evolutionary Algorithms and Applications (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Artificial Intelligence (24 citations), Computational Theory and Mathematics (4 citations), Computer Vision and Pattern Recognition (5 citations), Statistical and Nonlinear Physics (3 citations) and Management Information Systems (2 citations). Clare Lyle has collaborated with scholars based in United Kingdom, Canada and United States. Frequent co-authors include Marc G. Bellemare, Pablo Samuel Castro, Yarin Gal, Shagun Sodhani, Doina Precup, Dale Schuurmans, Mark van der Wilk, Tor Lattimore, Robert Dadashi and Angelos Filos. Their work appears in journals such as Nature, International Conference on Learning Representations, Proceedings of the AAAI Conference on Artificial Intelligence and Neural Information Processing Systems.
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.