Thore Graepel

ORCID

Publication Activity (10 Years)

Years Active: 1997-2022
Publications (10 Years): 73

Top Venues

Technical University of Berlin, Germany (PHD)

Education History

Technical University of Berlin, Germany

PHD

Publications

Kavya Kopparapu, Edgar A. Duéñez-Guzmán, Jayd Matyas, Alexander Sasha Vezhnevets, John P. Agapiou, Kevin R. McKee, Richard Everett, Janusz Marecki, Joel Z. Leibo, Thore Graepel
Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria. CoRR (2022)
Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess
From motor control to team play in simulated humanoid football. Sci. Robotics 7 (69) (2022)
Siqi Liu, Luke Marris, Daniel Hennes, Josh Merel, Nicolas Heess, Thore Graepel
NeuPL: Neural Population Learning. CoRR (2022)
Siqi Liu, Luke Marris, Daniel Hennes, Josh Merel, Nicolas Heess, Thore Graepel
NeuPL: Neural Population Learning. ICLR (2022)
Luke Marris, Marc Lanctot, Ian Gemp, Shayegan Omidshafiei, Stephen McAleer, Jerome T. Connor, Karl Tuyls, Thore Graepel
Game Theoretic Rating in N-player general-sum games with Equilibria. CoRR (2022)
Ian M. Gemp, Brian McWilliams, Claire Vernade, Thore Graepel
EigenGame Unloaded: When playing games is better than optimizing. ICLR (2022)
Luke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel
Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers. ICML (2021)
Yoram Bachrach, Ian M. Gemp, Marta Garnelo, János Kramár, Tom Eccles, Dan Rosenbaum, Thore Graepel
A Neural Network Auction For Group Decision Making Over a Continuous Space. IJCAI (2021)
Thore Graepel, Ralf Herbrich
A PAC-Bayesian Analysis of Distance-Based Classifiers: Why Nearest-Neighbour works! CoRR (2021)
Ian M. Gemp, Brian McWilliams, Claire Vernade, Thore Graepel
EigenGame Unloaded: When playing games is better than optimizing. CoRR (2021)
Ian M. Gemp, Brian McWilliams, Claire Vernade, Thore Graepel
EigenGame: PCA as a Nash Equilibrium. ICLR (2021)
Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome T. Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steele, Pauline Luc, Adrià Recasens, Alexandre Galashov, Gregory Thornton, Romuald Elie, Pablo Sprechmann, Pol Moreno, Kris Cao, Marta Garnelo, Praneet Dutta, Michal Valko, Nicolas Heess, Alex Bridgland, Julien Pérolat, Bart De Vylder, S. M. Ali Eslami, Mark Rowland, Andrew Jaegle, Rémi Munos, Trevor Back, Razia Ahamed, Simon Bouton, Nathalie Beauguerlange, Jackson Broshear, Thore Graepel, Demis Hassabis
Game Plan: What AI can do for Football, and What Football can do for AI. J. Artif. Intell. Res. 71 (2021)
Kevin R. McKee, Edward Hughes, Tina O. Zhu, Martin J. Chadwick, Raphael Koster, Antonio García Castañeda, Charlie Beattie, Thore Graepel, Matthew Botvinick, Joel Z. Leibo
Deep reinforcement learning models the emergent dynamics of human cooperation. CoRR (2021)
Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess
From Motor Control to Team Play in Simulated Humanoid Football. CoRR (2021)
Joel Z. Leibo, Edgar A. Duéñez-Guzmán, Alexander Sasha Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charles Beattie, Igor Mordatch, Thore Graepel
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. CoRR (2021)
Luke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel
Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers. CoRR (2021)
Joel Z. Leibo, Edgar A. Duéñez-Guzmán, Alexander Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. ICML (2021)
Ian M. Gemp, Brian McWilliams, Claire Vernade, Thore Graepel
EigenGame: PCA as a Nash Equilibrium. CoRR (2020)
Tobias Baumann, Thore Graepel, John Shawe-Taylor
Adaptive Mechanism Design: Learning to Promote Cooperation. IJCNN (2020)
David Balduzzi, Wojciech M. Czarnecki, Tom Anthony, Ian M. Gemp, Edward Hughes, Joel Z. Leibo, Georgios Piliouras, Thore Graepel
Smooth markets: A basic mechanism for organizing gradient-based learners. ICLR (2020)
Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian M. Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach
Learning to Play No-Press Diplomacy with Best Response Policy Iteration. NeurIPS (2020)
David Balduzzi, Wojciech M. Czarnecki, Thomas W. Anthony, Ian M. Gemp, Edward Hughes, Joel Z. Leibo, Georgios Piliouras, Thore Graepel
Smooth markets: A basic mechanism for organizing gradient-based learners. CoRR (2020)
Allan Dafoe, Edward Hughes, Yoram Bachrach, Tantum Collins, Kevin R. McKee, Joel Z. Leibo, Kate Larson, Thore Graepel
Open Problems in Cooperative AI. CoRR (2020)
Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Pérolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Rémi Munos
A Generalized Training Approach for Multiagent Learning. ICLR (2020)
Thore Graepel
Automatic Curricula in Deep Multi-Agent Reinforc ement Learning. AAMAS (2020)
Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome T. Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steele, Pauline Luc, Adrià Recasens, Alexandre Galashov, Gregory Thornton, Romuald Elie, Pablo Sprechmann, Pol Moreno, Kris Cao, Marta Garnelo, Praneet Dutta, Michal Valko, Nicolas Heess, Alex Bridgland, Julien Pérolat, Bart De Vylder, S. M. Ali Eslami, Mark Rowland, Andrew Jaegle, Rémi Munos, Trevor Back, Razia Ahamed, Simon Bouton, Nathalie Beauguerlange, Jackson Broshear, Thore Graepel, Demis Hassabis
Game Plan: What AI can do for Football, and What Football can do for AI. CoRR (2020)
Raphael Köster, Kevin R. McKee, Richard Everett, Laura Weidinger, William S. Isaac, Edward Hughes, Edgar A. Duéñez-Guzmán, Thore Graepel, Matthew Botvinick, Joel Z. Leibo
Model-free conventions in multi-agent reinforcement learning with heterogeneous preferences. CoRR (2020)
Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, Timothy P. Lillicrap, David Silver
Mastering Atari, Go, chess and shogi by planning with a learned model. Nat. 588 (7839) (2020)
Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian M. Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach
Learning to Play No-Press Diplomacy with Best Response Policy Iteration. CoRR (2020)
Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou, Joel Z. Leibo, Marc Lanctot, Michael Johanson, Wojciech M. Czarnecki, Thore Graepel
Negotiating Team Formation Using Deep Reinforcement Learning. CoRR (2020)
Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou, Joel Z. Leibo, Marc Lanctot, Michael Johanson, Wojciech M. Czarnecki, Thore Graepel
Negotiating team formation using deep reinforcement learning. Artif. Intell. 288 (2020)
Karl Tuyls, Julien Pérolat, Marc Lanctot, Edward Hughes, Richard Everett, Joel Z. Leibo, Csaba Szepesvári, Thore Graepel
Bounds and dynamics for empirical game theoretic analysis. Auton. Agents Multi Agent Syst. 34 (1) (2020)
David Balduzzi, Marta Garnelo, Yoram Bachrach, Wojciech M. Czarnecki, Julien Pérolat, Max Jaderberg, Thore Graepel
Open-ended Learning in Symmetric Zero-sum Games. CoRR (2019)
Tom Eccles, Yoram Bachrach, Guy Lever, Angeliki Lazaridou, Thore Graepel
Biases for Emergent Communication in Multi-agent Reinforcement Learning. NeurIPS (2019)
Tom Eccles, Yoram Bachrach, Guy Lever, Angeliki Lazaridou, Thore Graepel
Biases for Emergent Communication in Multi-agent Reinforcement Learning. CoRR (2019)
Dylan Banarse, Yoram Bachrach, Siqi Liu, Guy Lever, Nicolas Heess, Chrisantha Fernando, Pushmeet Kohli, Thore Graepel
The Body is Not a Given: Joint Agent Policy Learning and Morphology Evolution. AAMAS (2019)
Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, Timothy P. Lillicrap, David Silver
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model. CoRR (2019)
Alistair Letcher, David Balduzzi, Sébastien Racanière, James Martens, Jakob N. Foerster, Karl Tuyls, Thore Graepel
Differentiable Game Mechanics. J. Mach. Learn. Res. 20 (2019)
Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, János Kramár, Neil C. Rabinowitz, Thore Graepel, Matthew Botvinick, Peter W. Battaglia
Relational Forward Models for Multi-Agent Learning. ICLR (Poster) (2019)
Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel
Emergent Coordination Through Competition. CoRR (2019)
Alistair Letcher, David Balduzzi, Sébastien Racanière, James Martens, Jakob N. Foerster, Karl Tuyls, Thore Graepel
Differentiable Game Mechanics. CoRR (2019)
Joel Z. Leibo, Edward Hughes, Marc Lanctot, Thore Graepel
Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research. CoRR (2019)
Andrea Tacchetti, DJ Strouse, Marta Garnelo, Thore Graepel, Yoram Bachrach
A Neural Architecture for Designing Truthful and Efficient Auctions. CoRR (2019)
Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel
Emergent Coordination Through Competition. ICLR (Poster) (2019)
David Balduzzi, Marta Garnelo, Yoram Bachrach, Wojciech Czarnecki, Julien Pérolat, Max Jaderberg, Thore Graepel
Open-ended learning in symmetric zero-sum games. ICML (2019)
Peter Sunehag, Guy Lever, Siqi Liu, Josh Merel, Nicolas Heess, Joel Z. Leibo, Edward Hughes, Tom Eccles, Thore Graepel
Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems. ALIFE (2019)
Joel Z. Leibo, Julien Pérolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar A. Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel
Malthusian Reinforcement Learning. AAMAS (2019)
Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Pérolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Rémi Munos
A Generalized Training Approach for Multiagent Learning. CoRR (2019)
David Balduzzi, Sébastien Racanière, James Martens, Jakob N. Foerster, Karl Tuyls, Thore Graepel
The Mechanics of n-Player Differentiable Games. CoRR (2018)
David Balduzzi, Karl Tuyls, Julien Pérolat, Thore Graepel
Re-evaluating evaluation. NeurIPS (2018)
Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, Neil C. Rabinowitz, Thore Graepel, Matthew Botvinick, Peter W. Battaglia
Relational Forward Models for Multi-Agent Learning. CoRR (2018)
David Balduzzi, Sébastien Racanière, James Martens, Jakob N. Foerster, Karl Tuyls, Thore Graepel
The Mechanics of n-Player Differentiable Games. ICML (2018)
Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinícius Flores Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, Thore Graepel
Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward. AAMAS (2018)
Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel
A Generalised Method for Empirical Game Theoretic Analysis. AAMAS (2018)
Edward Hughes, Joel Z. Leibo, Matthew Phillips, Karl Tuyls, Edgar A. Duéñez-Guzmán, Antonio García Castañeda, Iain Dunning, Tina Zhu, Kevin R. McKee, Raphael Koster, Heather Roff, Thore Graepel
Inequity aversion improves cooperation in intertemporal social dilemmas. NeurIPS (2018)
Joel Z. Leibo, Julien Pérolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar A. Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel
Malthusian Reinforcement Learning. CoRR (2018)
Tobias Baumann, Thore Graepel, John Shawe-Taylor
Adaptive Mechanism Design: Learning to Promote Cooperation. CoRR (2018)
Karl Tuyls, Julien Pérolat, Marc Lanctot, Joel Z. Leibo, Thore Graepel
A Generalised Method for Empirical Game Theoretic Analysis. CoRR (2018)
David Balduzzi, Karl Tuyls, Julien Pérolat, Thore Graepel
Re-evaluating evaluation. CoRR (2018)
Max Jaderberg, Wojciech M. Czarnecki, Iain Dunning, Luke Marris, Guy Lever, Antonio García Castañeda, Charles Beattie, Neil C. Rabinowitz, Ari S. Morcos, Avraham Ruderman, Nicolas Sonnerat, Tim Green, Louise Deason, Joel Z. Leibo, David Silver, Demis Hassabis, Koray Kavukcuoglu, Thore Graepel
Human-level performance in first-person multiplayer games with population-based deep reinforcement learning. CoRR (2018)
Edward Hughes, Joel Z. Leibo, Matthew G. Philips, Karl Tuyls, Edgar A. Duéñez-Guzmán, Antonio García Castañeda, Iain Dunning, Tina Zhu, Kevin R. McKee, Raphael Koster, Heather Roff, Thore Graepel
Inequity aversion resolves intertemporal social dilemmas. CoRR (2018)
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy P. Lillicrap, Karen Simonyan, Demis Hassabis
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. CoRR (2017)
Joel Z. Leibo, Vinícius Flores Zambaldi, Marc Lanctot, Janusz Marecki, Thore Graepel
Multi-agent Reinforcement Learning in Sequential Social Dilemmas. AAMAS (2017)
Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel
A multi-agent reinforcement learning model of common-pool resource appropriation. NIPS (2017)
Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel
A multi-agent reinforcement learning model of common-pool resource appropriation. CoRR (2017)
Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. CoRR (2017)
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy P. Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, Demis Hassabis
Mastering the game of Go without human knowledge. Nat. 550 (7676) (2017)
Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinícius Flores Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, Thore Graepel
Value-Decomposition Networks For Cooperative Multi-Agent Learning. CoRR (2017)
Karl Tuyls, Julien Pérolat, Marc Lanctot, Georg Ostrovski, Rahul Savani, Joel Z. Leibo, Toby Ord, Thore Graepel, Shane Legg
Symmetric Decomposition of Asymmetric Games. CoRR (2017)
Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. NIPS (2017)
Joel Z. Leibo, Vinícius Flores Zambaldi, Marc Lanctot, Janusz Marecki, Thore Graepel
Multi-agent Reinforcement Learning in Sequential Social Dilemmas. CoRR (2017)
David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Vedavyas Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy P. Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, Demis Hassabis
Mastering the game of Go with deep neural networks and tree search. Nat. 529 (7587) (2016)
Diana Borsa, Thore Graepel, John Shawe-Taylor
Learning Shared Representations in Multi-task Reinforcement Learning. CoRR (2016)
Diana Borsa, Thore Graepel, Andrew D. Gordon
The Wreath Process: A totally generative model of geometric shape based on nested symmetries. CoRR (2015)
Andrew D. Gordon, Claudio V. Russo, Marcin Szymczak, Johannes Borgström, Nicolas Rolland, Thore Graepel, Daniel Tarlow
Probabilistic Programs as Spreadsheet Queries. ESOP (2015)
Andrew D. Gordon, Thore Graepel, Nicolas Rolland, Claudio V. Russo, Johannes Borgström, John Guiver
Tabular: a schema-driven probabilistic programming language. POPL (2014)
Sandro Bauer, Stephen Clark, Thore Graepel
Learning to Identify Historical Figures for Timeline Creation from Wikipedia Articles. SocInfo Workshops (2014)
Michal Kosinski, Yoram Bachrach, Pushmeet Kohli, David Stillwell, Thore Graepel
Manifestations of user personality in website choice and behaviour on online social networks. Mach. Learn. 95 (3) (2014)
Aaron Defazio, Thore Graepel
A Comparison of learning algorithms on the Arcade Learning Environment. CoRR (2014)
Sandro Bauer, Stephen Clark, Laura Rimell, Thore Graepel
Learning a Theory of Marriage (and Other Relations) from a Web Corpus. ECIR (2014)
Yoram Bachrach, Thore Graepel, Pushmeet Kohli, Michal Kosinski, David Stillwell
Your digital image: factors behind demographic and psychometric predictions from social network profiles. AAMAS (2014)
Andrew D. Gordon, Mihhail Aizatulin, Johannes Borgström, Guillaume Claret, Thore Graepel, Aditya V. Nori, Sriram K. Rajamani, Claudio V. Russo
A model-learner pattern for bayesian reasoning. POPL (2013)
Bin Bi, Milad Shokouhi, Michal Kosinski, Thore Graepel
Inferring the demographics of search users: social data meets search queries. WWW (2013)
Simon Lacoste-Julien, Konstantina Palla, Alex Davies, Gjergji Kasneci, Thore Graepel, Zoubin Ghahramani
SIGMa: simple greedy matching for aligning large knowledge bases. KDD (2013)
Sameer Singh, Thore Graepel
Automated probabilistic modeling for relational data. CIKM (2013)
Pushmeet Kohli, Michael J. Kearns, Yoram Bachrach, Ralf Herbrich, David Stillwell, Thore Graepel
Colonel Blotto on Facebook: the effect of social relations on strategic interaction. WebSci (2012)
Simon Lacoste-Julien, Konstantina Palla, Alex Davies, Gjergji Kasneci, Thore Graepel, Zoubin Ghahramani
SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases CoRR (2012)
Tim Salimans, Ulrich Paquet, Thore Graepel
Collaborative learning of preference rankings. RecSys (2012)
Sameer Singh, Thore Graepel
Compiling Relational Database Schemata into Probabilistic Graphical Models CoRR (2012)
Yoram Bachrach, Thore Graepel, Tom Minka, John Guiver
How To Grade a Test Without Knowing the Answers - A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing. ICML (2012)
Thore Graepel, Kristin E. Lauter, Michael Naehrig
ML Confidential: Machine Learning on Encrypted Data. ICISC (2012)
Yoram Bachrach, Thore Graepel, Gjergji Kasneci, Michal Kosinski, Jurgen Van Gael
Crowd IQ: aggregating opinions to boost performance. AAMAS (2012)
Michal Kosinski, Yoram Bachrach, Gjergji Kasneci, Jurgen Van Gael, Thore Graepel
Crowd IQ: measuring the intelligence of crowdsourcing platforms. WebSci (2012)
Xi Alice Gao, Yoram Bachrach, Peter B. Key, Thore Graepel
Quality Expectation-Variance Tradeoffs in Crowdsourcing Contests. AAAI (2012)
Yoram Bachrach, Michal Kosinski, Thore Graepel, Pushmeet Kohli, David Stillwell
Personality and patterns of Facebook usage. WebSci (2012)
Shengbo Guo, Scott Sanner, Thore Graepel, Wray L. Buntine
Score-Based Bayesian Skill Learning. ECML/PKDD (1) (2012)
Thore Graepel, Kristin E. Lauter, Michael Naehrig
ML Confidential: Machine Learning on Encrypted Data. IACR Cryptol. ePrint Arch. 2012 (2012)
Philipp Hennig, David H. Stern, Ralf Herbrich, Thore Graepel
Kernel Topic Models. AISTATS (2012)
Philipp Hennig, David H. Stern, Ralf Herbrich, Thore Graepel
Kernel Topic Models CoRR (2011)
Yan Xu, Xiang Cao, Abigail Sellen, Ralf Herbrich, Thore Graepel
Sociable killers: understanding social relationships in an online first-person shooter game. CSCW (2011)

Thore Graepel.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Thore Graepel