Thore Graepel
Impact in
- Artificial Intelligence top 0.02%
- Reinforcement Learning in Robotics
- Artificial Intelligence in Games
- Evolutionary Algorithms and Applications
- Adversarial Robustness in Machine Learning
- Neural Networks and Applications
- Health Informatics top 0.5%
Papers in
-
- Machine Learning and Algorithms 22
- Reinforcement Learning in Robotics 13
- Artificial Intelligence in Games 12
- Neural Networks and Applications 11
- Machine Learning and Data Classification 9
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- Advanced Bandit Algorithms Research 9
- Co-authors
- David Silver (4 shared papers)Demis Hassabis (4 shared papers)Timothy Lillicrap (3 shared papers)Julian Schrittwieser (3 shared papers)Laurent Sifre (3 shared papers)Arthur Guez (3 shared papers)Ioannis Antonoglou (3 shared papers)George van den Driessche (2 shared papers)
- Journals
- Nature (4 papers)Machine Learning (3 papers)Science (2 papers)ACM SIGPLAN Notices (2 papers)Journal of Machine Learning Research (2 papers)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Thore Graepel
102 papers receiving 20.0k citations
Thore Graepel's Hit Papers
Peers
Comparison fields: 5 of 215
- Artificial Intelligence 10.7k
- Health Informatics 225
- Computer Vision and Pattern Recognition 2.9k
- Management Science and Operations Research 1.4k
- Computational Theory and Mathematics 1.5k
Countries citing papers authored by Thore Graepel
This map shows the geographic impact of Thore Graepel'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 Thore Graepel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thore Graepel more than expected).
Fields of papers citing papers by Thore Graepel
This network shows the impact of papers produced by Thore Graepel. 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 Thore Graepel. The network helps show where Thore Graepel may publish in the future.
Co-authors
The 25 scholars most cited alongside Thore Graepel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 104 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Mastering the game of Go with deep neural networks and tree search Hit paper breakdown → | 2016 | 8961 |
| 2 | Mastering the game of Go without human knowledge Hit paper breakdown → | 2017 | 5141 |
| 3 | A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play Hit paper breakdown → | 2018 | 1882 |
| 4 | Private traits and attributes are predictable from digital records of human behavior Hit paper breakdown → | 2013 | 1568 |
| 5 | Human-level performance in 3D multiplayer games with population-based reinforcement learning Hit paper breakdown → | 2019 | 358 |
| 6 | Web-Scale Bayesian Click-Through rate Prediction for Sponsored Search Advertising in Microsoft's Bing Search Engine | 2010 | 266 |
| 7 | 2018 | 240 | |
| 8 | 2012 | 239 | |
| 9 | 2013 | 164 | |
| 10 | 2009 | 157 | |
| 11 | Generalization Bounds for the Area Under the ROC Curve | 2005 | 146 |
| 12 | 2021 | 128 | |
| 13 | Classification on Pairwise Proximity Data | 1998 | 97 |
| 14 | 2012 | 93 | |
| 15 | 2013 | 79 | |
| 16 | 2000 | 75 | |
| 17 | 1998 | 75 | |
| 18 | 1997 | 61 | |
| 19 | TrueSkill Through Time: Revisiting the History of Chess | 2007 | 59 |
| 20 | 2017 | 59 |
About Thore Graepel
Thore Graepel is a scholar working on Artificial Intelligence, Management Science and Operations Research, Computer Vision and Pattern Recognition, Sociology and Political Science and Statistical and Nonlinear Physics, having authored 104 papers that have together received 21.0k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (22 papers), Reinforcement Learning in Robotics (13 papers), Artificial Intelligence in Games (12 papers), Neural Networks and Applications (11 papers), Experimental Behavioral Economics Studies (10 papers), Face and Expression Recognition (9 papers), Machine Learning and Data Classification (9 papers) and Advanced Bandit Algorithms Research (9 papers). The work is most often cited by research in Artificial Intelligence (10.7k citations), Health Informatics (225 citations), Computer Vision and Pattern Recognition (2.9k citations), Management Science and Operations Research (1.4k citations) and Computational Theory and Mathematics (1.5k citations). Thore Graepel has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include David Silver, Demis Hassabis, Timothy Lillicrap, Julian Schrittwieser, Laurent Sifre, Arthur Guez, Ioannis Antonoglou, George van den Driessche, Aja Huang and Michał Kosiński. Their work appears in journals such as Nature, Machine Learning, Science, ACM SIGPLAN Notices and Journal of Machine Learning Research.
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.