Thore Graepel

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Bendraautoriai

Ralf HerbrichHasso Plattner InstitutePatvirtintas el. paštas hpi.de
Marc LanctotResearch Scientist, Google DeepMindPatvirtintas el. paštas google.com
David SilverDeepMind, UCLPatvirtintas el. paštas google.com
Laurent SifreH CompanyPatvirtintas el. paštas polytechnique.edu
Arthur GuezGoogle DeepMindPatvirtintas el. paštas google.com
Joel Z LeiboResearch scientistPatvirtintas el. paštas google.com
Timothy P. LillicrapDirector of Research, Google DeepMindPatvirtintas el. paštas google.com
Yoram BachrachMeta (FAIR)Patvirtintas el. paštas meta.com
Klaus ObermayerProfessor, Fakultät IV - Electrical Engineering and Computer Science, Technische Universität BerlinPatvirtintas el. paštas tu-berlin.de
Karl TuylsResearch Scientist, Entrepreneur, ex-Google DeepMind, Prof at University of LiverpoolPatvirtintas el. paštas hcompany.ai
Thomas HubertGoogle DeepmindPatvirtintas el. paštas google.com
Michal KosinskiStanford UniversityPatvirtintas el. paštas stanford.edu
Karen SimonyanChief Scientist, Microsoft AIPatvirtintas el. paštas microsoft.com
Chris J. MaddisonUniversity of TorontoPatvirtintas el. paštas cs.toronto.edu
Matthew LaiDeepMindPatvirtintas el. paštas google.com
David StillwellCambridge UniversityPatvirtintas el. paštas cam.ac.uk
koray kavukcuogluDeepMindPatvirtintas el. paštas kavukcuoglu.org
julien perolatDeepMindPatvirtintas el. paštas google.com
Aja HuangDeepMindPatvirtintas el. paštas google.com
Vinicius ZambaldiGoogle DeepmindPatvirtintas el. paštas google.com

Stebėti

Thore Graepel

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

Patvirtintas el. paštas ucl.ac.uk - Pagrindinis puslapis

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


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
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	20534	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	11661	2017
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	4949	2018
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	3998	2013
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	2634	2020
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	2430	2017
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	1939	2017
Large margin rank boundaries for ordinal regression R Herbrich, T Graepel, K Obermayer	1477	2000
TrueSkill™: a Bayesian skill rating system R Herbrich, T Minka, T Graepel Advances in neural information processing systems 19, 2006	1112	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	1019	2019
Multi-agent reinforcement learning in sequential social dilemmas JZ Leibo, V Zambaldi, M Lanctot, J Marecki, T Graepel arXiv preprint arXiv:1702.03037, 2017	936	2017
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	778	2017
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	746	2010
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	675	2012
ML confidential: Machine learning on encrypted data T Graepel, K Lauter, M Naehrig International conference on information security and cryptology, 1-21, 2012	656	2012
Support vector learning for ordinal regression R Herbrich, T Graepel, K Obermayer IET Digital Library, 1999	587	1999
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	456	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	369	2009
Bayes point machines R Herbrich, T Graepel, C Campbell Journal of Machine Learning Research 1 (Aug), 245-279, 2001	340	2001
The mechanics of n-player differentiable games D Balduzzi, S Racaniere, J Martens, J Foerster, K Tuyls, T Graepel International Conference on Machine Learning, 354-363, 2018	329	2018

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