Thore Graepel

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Ralf HerbrichHasso Plattner InstituteEmail confirmado em hpi.de
Marc LanctotResearch Scientist, DeepMindEmail confirmado em google.com
David SilverDeepMind, UCLEmail confirmado em google.com
Laurent SifreGoogle DeepMindEmail confirmado em polytechnique.edu
Arthur GuezGoogle DeepMindEmail confirmado em google.com
Yoram BachrachDeepMindEmail confirmado em google.com
Timothy P. LillicrapSenior Research Scientist, Google DeepMindEmail confirmado em google.com
Joel Z LeiboResearch scientistEmail confirmado em google.com
Klaus ObermayerProfessor, Fakultät IV - Electrical Engineering and Computer Science, Technische Universität BerlinEmail confirmado em tu-berlin.de
Karl TuylsResearch Scientist, Google DeepMind and Professor of computer science, University of LiverpoolEmail confirmado em google.com
Chris J. MaddisonUniversity of TorontoEmail confirmado em cs.toronto.edu
Aja HuangDeepMindEmail confirmado em google.com
Michal KosinskiStanford UniversityEmail confirmado em stanford.edu
Karen SimonyanCo-Founder and Chief Scientist at Inflection AIEmail confirmado em inflection.ai
Thomas HubertGoogle DeepmindEmail confirmado em google.com
David StillwellCambridge UniversityEmail confirmado em cam.ac.uk
koray kavukcuogluDeepMindEmail confirmado em kavukcuoglu.org
Matthew LaiDeepMindEmail confirmado em matthewlai.ca
julien perolatDeepMindEmail confirmado em google.com
Pushmeet KohliDeepMindEmail confirmado em google.com

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Thore Graepel

Global Lead Computational Science, AI & ML at Altos Labs and Chair of Machine Learning, UCL

Email confirmado em ucl.ac.uk - Página inicial

Machine Learning Reinforcement Learning Deep Learning Multi-Agent Learning Computational Biology


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Mastering the game of Go with deep neural networks and tree search D Silver, A Huang, CJ Maddison, A Guez, L Sifre, G Van Den Driessche, ... nature 529 (7587), 484-489, 2016	15331	2016
Mastering the game of go without human knowledge D Silver, J Schrittwieser, K Simonyan, I Antonoglou, A Huang, A Guez, ... nature 550 (7676), 354-359, 2017	8599	2017
Private traits and attributes are predictable from digital records of human behavior M Kosinski, D Stillwell, T Graepel Proceedings of the national academy of sciences 110 (15), 5802-5805, 2013	3338	2013
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play D Silver, T Hubert, J Schrittwieser, I Antonoglou, M Lai, A Guez, M Lanctot, ... Science 362 (6419), 1140-1144, 2018	3078	2018
Mastering chess and shogi by self-play with a general reinforcement learning algorithm D Silver, T Hubert, J Schrittwieser, I Antonoglou, M Lai, A Guez, M Lanctot, ... arXiv preprint arXiv:1712.01815, 2017	1661	2017
Large margin rank boundaries for ordinal regression R Herbrich Advances in large margin classifiers, 115-132, 2000	1405	2000
Mastering atari, go, chess and shogi by planning with a learned model J Schrittwieser, I Antonoglou, T Hubert, K Simonyan, L Sifre, S Schmitt, ... Nature 588 (7839), 604-609, 2020	1380	2020
Value-decomposition networks for cooperative multi-agent learning P Sunehag, G Lever, A Gruslys, WM Czarnecki, V Zambaldi, M Jaderberg, ... arXiv preprint arXiv:1706.05296, 2017	979	2017
TrueSkill™: a Bayesian skill rating system R Herbrich, T Minka, T Graepel Advances in neural information processing systems 19, 2006	919	2006
Human-level performance in 3D multiplayer games with population-based reinforcement learning M Jaderberg, WM Czarnecki, I Dunning, L Marris, G Lever, AG Castaneda, ... Science 364 (6443), 859-865, 2019	697	2019
Web-scale bayesian click-through rate prediction for sponsored search advertising in microsoft's bing search engine T Graepel, JQ Candela, T Borchert, R Herbrich Omnipress 27, 13-20, 2010	673	2010
Multi-agent reinforcement learning in sequential social dilemmas JZ Leibo, V Zambaldi, M Lanctot, J Marecki, T Graepel arXiv preprint arXiv:1702.03037, 2017	612	2017
Personality and patterns of Facebook usage Y Bachrach, M Kosinski, T Graepel, P Kohli, D Stillwell Proceedings of the 4th annual ACM web science conference, 24-32, 2012	601	2012
Support vector learning for ordinal regression R Herbrich, T Graepel, K Obermayer IET Digital Library, 1999	563	1999
ML confidential: Machine learning on encrypted data T Graepel, K Lauter, M Naehrig Information Security and Cryptology–ICISC 2012: 15th International …, 2013	548	2013
A unified game-theoretic approach to multiagent reinforcement learning M Lanctot, V Zambaldi, A Gruslys, A Lazaridou, K Tuyls, J Pérolat, D Silver, ... Advances in neural information processing systems 30, 2017	531	2017
Manifestations of user personality in website choice and behaviour on online social networks M Kosinski, Y Bachrach, P Kohli, D Stillwell, T Graepel Machine learning 95, 357-380, 2014	391	2014
Matchbox: large scale online bayesian recommendations DH Stern, R Herbrich, T Graepel Proceedings of the 18th international conference on World wide web, 111-120, 2009	354	2009
Bayes point machines R Herbrich, T Graepel, C Campbell Journal of Machine Learning Research 1 (Aug), 245-279, 2001	321	2001
Generalization Bounds for the Area Under the ROC Curve. S Agarwal, T Graepel, R Herbrich, S Har-Peled, D Roth, MI Jordan Journal of Machine Learning Research 6 (4), 2005	286	2005

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