Tom Eccles
Impact in
- Information Systems top 2%
- Software Engineering Research
- Software top 5%
- Software Testing and Debugging Techniques
Papers in
-
- Game Theory and Applications 2
- Auction Theory and Applications 2
-
- Reinforcement Learning in Robotics 4
- Artificial Intelligence in Games 2
- Multi-Agent Systems and Negotiation 1
- Co-authors
- Thore Graepel (3 shared papers)János Kramár (6 shared papers)Béla Bollobás (2 shared papers)Joel Z. Leibo (3 shared papers)Andrea Tacchetti (4 shared papers)Yoram Bachrach (5 shared papers)Edward Hughes (3 shared papers)Kevin R. McKee (1 shared paper)
- Journals
- Science (2 papers)Nature Communications (1 paper)Journal of Combinatorial Theory Series A (1 paper)Combinatorics Probability Computing (1 paper)Journal of Graph Theory (1 paper)
- Partner nations
- United KingdomUnited States
In The Last Decade
Tom Eccles
12 papers receiving 795 citations
Tom Eccles's Hit Papers
Peers
Comparison fields: 5 of 77
- Information Systems 356
- Software 53
- Computer Science Applications 51
- Artificial Intelligence 287
- Health Informatics 13
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 19 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 | Competition-level code generation with AlphaCode Hit paper breakdown → | 2022 | 652 |
| 2 | 2022 | 93 | |
| 3 | 2015 | 25 | |
| 4 | 2022 | 14 | |
| 5 | 2019 | 12 | |
| 6 | 2012 | 9 | |
| 7 | 2019 | 4 | |
| 8 | 2020 | 4 | |
| 9 | 2021 | 3 | |
| 10 | 2022 | 3 | |
| 11 | 2015 | 1 | |
| 12 | 2021 | 1 | |
| 13 | 2022 | 0 |
About Tom Eccles
Tom Eccles is a scholar working on Management Science and Operations Research, Artificial Intelligence, Discrete Mathematics and Combinatorics, Computational Theory and Mathematics and Sociology and Political Science, having authored 13 papers that have together received 821 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (4 papers), Advanced Combinatorial Mathematics (2 papers), Artificial Intelligence in Games (2 papers), Evolutionary Game Theory and Cooperation (2 papers), Game Theory and Applications (2 papers), Auction Theory and Applications (2 papers), Multi-Agent Systems and Negotiation (1 paper) and Graph Labeling and Dimension Problems (1 paper). The work is most often cited by research in Information Systems (356 citations), Software (53 citations), Computer Science Applications (51 citations), Artificial Intelligence (287 citations) and Health Informatics (13 citations). Tom Eccles has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Thore Graepel, János Kramár, Béla Bollobás, Joel Z. Leibo, Andrea Tacchetti, Yoram Bachrach, Edward Hughes, Kevin R. McKee, Mateusz Malinowski and Guy Lever. Their work appears in journals such as Science, Nature Communications, Journal of Combinatorial Theory Series A, Combinatorics Probability Computing and Journal of Graph Theory.
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.