Tom Eccles
Impact in
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- Graph Labeling and Dimension Problems
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- Experimental Behavioral Economics Studies
Papers in
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- Reinforcement Learning in Robotics 2
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- Reservoir Engineering and Simulation Methods 4
- Enhanced Oil Recovery Techniques 3
- Co-authors
- Thore Graepel (5 shared papers)Yoram Bachrach (4 shared papers)Löıc Matthey (1 shared paper)Béla Bollobás (2 shared papers)Irina Higgins (1 shared paper)Christopher Burgess (1 shared paper)Alessandro Achille (1 shared paper)Nicholas Watters (1 shared paper)
- Journals
- Scientific Reports (1 paper)Journal of Graph Theory (1 paper)Nature Communications (1 paper)Journal of Combinatorial Theory Series A (1 paper)Combinatorics Probability Computing (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Tom Eccles
14 papers receiving 87 citations
Peers
Comparison fields: 5 of 50
- Computational Theory and Mathematics 28
- Safety Research 10
- Acoustics and Ultrasonics 1
- Artificial Intelligence 32
- Management Science and Operations Research 8
Countries citing papers authored by Tom Eccles
This map shows the geographic impact of Tom Eccles'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 Tom Eccles with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Eccles more than expected).
Fields of papers citing papers by Tom Eccles
This network shows the impact of papers produced by Tom Eccles. 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 Tom Eccles. The network helps show where Tom Eccles may publish in the future.
Co-authors
The 25 scholars most cited alongside Tom Eccles, 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 | 2015 | 22 | |
| 2 | Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies | 2018 | 18 |
| 3 | 2022 | 11 | |
| 4 | 2019 | 11 | |
| 5 | 2012 | 6 | |
| 6 | 2019 | 6 | |
| 7 | 2019 | 4 | |
| 8 | 2008 | 4 | |
| 9 | 2009 | 3 | |
| 10 | 2021 | 2 | |
| 11 | 2009 | 2 | |
| 12 | 2022 | 1 | |
| 13 | 2015 | 1 | |
| 14 | 1983 | 1 |
About Tom Eccles
Tom Eccles is a scholar working on Artificial Intelligence, Ocean Engineering, Mechanical Engineering, Discrete Mathematics and Combinatorics and Computational Theory and Mathematics, having authored 14 papers that have together received 92 indexed citations. Recurring topics across this work include Reservoir Engineering and Simulation Methods (4 papers), Hydraulic Fracturing and Reservoir Analysis (3 papers), Limits and Structures in Graph Theory (3 papers), Enhanced Oil Recovery Techniques (3 papers), Auction Theory and Applications (2 papers), Reinforcement Learning in Robotics (2 papers), Advanced Graph Theory Research (2 papers) and Mathematical Dynamics and Fractals (1 paper). The work is most often cited by research in Computational Theory and Mathematics (28 citations), Safety Research (10 citations), Acoustics and Ultrasonics (1 citation), Artificial Intelligence (32 citations) and Management Science and Operations Research (8 citations). Tom Eccles has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Thore Graepel, Yoram Bachrach, Löıc Matthey, Béla Bollobás, Irina Higgins, Christopher Burgess, Alessandro Achille, Nicholas Watters, Guy Lever and Alexander Lerchner. Their work appears in journals such as Scientific Reports, Journal of Graph Theory, Nature Communications, Journal of Combinatorial Theory Series A and Combinatorics Probability Computing.
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.