Tom Eccles

681 total citations
14 papers, 92 citations indexed

About

Tom Eccles is a scholar working on Artificial Intelligence, Ocean Engineering and Mechanical Engineering. According to data from OpenAlex, Tom Eccles has authored 14 papers receiving a total of 92 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Ocean Engineering and 4 papers in Mechanical Engineering. Recurrent topics in Tom Eccles's work include Reservoir Engineering and Simulation Methods (4 papers), Limits and Structures in Graph Theory (3 papers) and Enhanced Oil Recovery Techniques (3 papers). Tom Eccles is often cited by papers focused on Reservoir Engineering and Simulation Methods (4 papers), Limits and Structures in Graph Theory (3 papers) and Enhanced Oil Recovery Techniques (3 papers). Tom Eccles collaborates with scholars based in United Kingdom, United States and Germany. Tom Eccles's co-authors include Thore Graepel, Yoram Bachrach, Irina Higgins, Alexander Lerchner, Alessandro Achille, Béla Bollobás, Löıc Matthey, Guy Lever, Nicholas Watters and Christopher Burgess and has published in prestigious journals such as Nature Communications, Scientific Reports and Journal of Combinatorial Theory Series A.

In The Last Decade

Tom Eccles

14 papers receiving 87 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Tom Eccles United Kingdom 6 32 28 10 10 9 14 92
Jan Pfeifer United States 4 44 1.4× 8 0.3× 11 1.1× 3 0.3× 6 0.7× 6 69
Aldo Pacchiano United States 4 53 1.7× 6 0.2× 10 1.0× 10 1.0× 3 0.3× 19 66
François Schwarzentruber France 9 179 5.6× 44 1.6× 9 0.9× 4 0.4× 25 2.8× 42 206
Jonathan Weed United States 5 24 0.8× 13 0.5× 17 1.7× 5 0.6× 10 94
Hadi Daneshmand Switzerland 7 55 1.7× 7 0.3× 20 2.0× 7 0.8× 8 96
Blake Woodworth United States 5 70 2.2× 5 0.2× 6 0.6× 7 0.7× 17 1.9× 9 94
Jiechuan Jiang China 3 47 1.5× 6 0.2× 6 0.6× 2 0.2× 13 1.4× 5 54
Ocan Sankur France 6 39 1.2× 50 1.8× 6 0.6× 8 0.9× 16 78
Yuqi Huang China 5 16 0.5× 12 0.4× 10 1.0× 1 0.1× 4 0.4× 9 65
Lorenz Minder United States 5 48 1.5× 16 0.6× 6 0.6× 43 4.8× 9 83

Countries citing papers authored by Tom Eccles

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Tom Eccles

This figure shows the co-authorship network connecting the top 25 collaborators of Tom Eccles. A scholar is included among the top collaborators of Tom Eccles based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tom Eccles. Tom Eccles is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Anthony, T, et al.. (2022). Designing all-pay auctions using deep learning and multi-agent simulation. Scientific Reports. 12(1). 16937–16937. 1 indexed citations
2.
Kramár, János, Tom Eccles, Andrea Tacchetti, et al.. (2022). Negotiation and honesty in artificial intelligence methods for the board game of Diplomacy. Nature Communications. 13(1). 7214–7214. 11 indexed citations
3.
Bachrach, Yoram, Marta Garnelo, János Kramár, et al.. (2021). A Neural Network Auction For Group Decision Making Over a Continuous Space. 4976–4979. 2 indexed citations
4.
Sunehag, Peter, Guy Lever, Siqi Liu, et al.. (2019). Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems. 4 indexed citations
5.
Sunehag, Peter, Guy Lever, Josh Merel, et al.. (2019). Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems. 6 indexed citations
6.
Eccles, Tom, Yoram Bachrach, Guy Lever, Angeliki Lazaridou, & Thore Graepel. (2019). Biases for Emergent Communication in Multi-agent Reinforcement Learning. arXiv (Cornell University). 32. 13111–13121. 11 indexed citations
7.
Achille, Alessandro, Tom Eccles, Löıc Matthey, et al.. (2018). Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies. Neural Information Processing Systems. 31. 9873–9883. 18 indexed citations
8.
Bollobás, Béla & Tom Eccles. (2015). Partial Shadows of Set Systems. Combinatorics Probability Computing. 24(5). 825–828. 1 indexed citations
9.
Eccles, Tom. (2015). Graphs of Large Linear Size Are Antimagic. Journal of Graph Theory. 81(3). 236–261. 22 indexed citations
10.
Bollobás, Béla, et al.. (2012). Union-closed families of sets. Journal of Combinatorial Theory Series A. 120(3). 531–544. 6 indexed citations
11.
12.
13.
Beckner, B. L., et al.. (2008). Adaptive Parallel Reservoir Simulation. International Petroleum Technology Conference. 4 indexed citations
14.

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.

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