Thomas Hubert

14.3k total citations · 3 hit papers
5 papers, 7.1k citations indexed

About

Thomas Hubert is a scholar working on Artificial Intelligence, Computational Mathematics and Computational Theory and Mathematics. According to data from OpenAlex, Thomas Hubert has authored 5 papers receiving a total of 7.1k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 1 paper in Computational Mathematics and 1 paper in Computational Theory and Mathematics. Recurrent topics in Thomas Hubert's work include Reinforcement Learning in Robotics (4 papers), Artificial Intelligence in Games (4 papers) and Evolutionary Algorithms and Applications (2 papers). Thomas Hubert is often cited by papers focused on Reinforcement Learning in Robotics (4 papers), Artificial Intelligence in Games (4 papers) and Evolutionary Algorithms and Applications (2 papers). Thomas Hubert collaborates with scholars based in United Kingdom, Canada and United States. Thomas Hubert's co-authors include David Silver, Julian Schrittwieser, Demis Hassabis, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Karen Simonyan, Timothy Lillicrap, Laurent Sifre and Thore Graepel and has published in prestigious journals such as Nature, Science and International Conference on Machine Learning.

In The Last Decade

Thomas Hubert

5 papers receiving 6.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Mastering the game of Go without human knowledge

2017 5.0k citations David Silver, Julian Schrittwieser et al. Nature profile →
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play

2018 1.8k citations David Silver, Thomas Hubert et al. Science profile →
Discovering faster matrix multiplication algorithms with reinforcement learning

2022 244 citations Alhussein Fawzi, Matej Balog et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Thomas Hubert United Kingdom	5	3.7k	1.0k	926	835	582	5	7.1k
Matthew Lai United Kingdom	5	3.7k 1.0×	999 1.0×	978 1.1×	846 1.0×	553 1.0×	8	7.1k
Chris J. Maddison United Kingdom	8	4.8k 1.3×	1.5k 1.4×	1.4k 1.6×	1.0k 1.2×	704 1.2×	13	9.0k
Yutian Chen China	13	2.8k 0.8×	826 0.8×	737 0.8×	662 0.8×	420 0.7×	57	5.5k
Hui Fan China	15	2.7k 0.7×	835 0.8×	1.3k 1.4×	645 0.8×	402 0.7×	75	6.1k
Dominik Grewe United Kingdom	7	4.7k 1.3×	1.5k 1.4×	1.4k 1.5×	1.0k 1.2×	707 1.2×	8	9.0k
Lucas Baker United States	5	2.6k 0.7×	775 0.8×	692 0.7×	626 0.7×	391 0.7×	9	5.1k
Sander Dieleman Belgium	13	5.2k 1.4×	1.5k 1.5×	2.2k 2.4×	1.0k 1.2×	712 1.2×	22	10.5k
Kevin P. Murphy Canada	25	3.9k 1.0×	898 0.9×	1.6k 1.8×	963 1.2×	403 0.7×	38	10.1k
Jinghong Li China	5	2.4k 0.6×	1.5k 1.5×	642 0.7×	1.3k 1.6×	555 1.0×	11	6.4k
Joëlle Pineau Canada	39	4.6k 1.2×	720 0.7×	1.7k 1.9×	1.2k 1.4×	470 0.8×	163	8.2k

Countries citing papers authored by Thomas Hubert

Since Specialization

Citations

This map shows the geographic impact of Thomas Hubert'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 Thomas Hubert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Hubert more than expected).

Fields of papers citing papers by Thomas Hubert

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas Hubert. 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 Thomas Hubert. The network helps show where Thomas Hubert may publish in the future.

Co-authorship network of co-authors of Thomas Hubert

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Hubert. A scholar is included among the top collaborators of Thomas Hubert 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 Thomas Hubert. Thomas Hubert is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

5 of 5 papers shown

1.

Fawzi, Alhussein, Matej Balog, Aja Huang, et al.. (2022). Discovering faster matrix multiplication algorithms with reinforcement learning. Nature. 610(7930). 47–53. 244 indexed citations breakdown →

2.

Bard, Nolan, Edward Lockhart, Marc Lanctot, et al.. (2022). Approximate Exploitability: Learning a Best Response. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 3487–3493. 6 indexed citations

3.

Hubert, Thomas, Julian Schrittwieser, Ioannis Antonoglou, et al.. (2021). Learning and Planning in Complex Action Spaces. International Conference on Machine Learning. 4476–4486. 7 indexed citations

4.

Silver, David, Thomas Hubert, Julian Schrittwieser, et al.. (2018). A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. Science. 362(6419). 1140–1144. 1827 indexed citations breakdown →

5.

Silver, David, Julian Schrittwieser, Karen Simonyan, et al.. (2017). Mastering the game of Go without human knowledge. Nature. 550(7676). 354–359. 5038 indexed citations breakdown →

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.

Explore authors with similar magnitude of impact