Marc Toussaint - Google Scholar Citations

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Christian IgelDepartment of Computer Science, University of CopenhagenVerified email at diku.dk
Nikolay JetchevSenior Research Scientist at ZalandoVerified email at zalando.de
Sethu VijayakumarProfessor of Robotics, University of Edinburgh; Programme Co-Director at The Alan Turing InstituteVerified email at ed.ac.uk
Michael GiengerHonda Research Institute EuropeVerified email at honda-ri.de
Manuel LopesInstituto Superior Tecnico, INESC-IDVerified email at tecnico.ulisboa.pt
Amos StorkeySchool of Informatics, University of EdinburghVerified email at ed.ac.uk
Peter EnglertUniversity of Southern CaliforniaVerified email at usc.edu
Ngo Anh VienLecturer (i.e. Assistant Professor), Queen's University BelfastVerified email at qub.ac.uk
Johannes KulickApplied Scientist at Amazon BerlinVerified email at amazon.com
Stefan SchaalComputer Scientist in Robotics and AIVerified email at google.com
Konrad RawlikPostdoctoral Fellow, Roslin Institute, University of EdinburghVerified email at sms.ed.ac.uk
Duy Nguyen-TuongBosch Center for AI, GermanyVerified email at robot-learning.de
Shlomo ZilbersteinProfessor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
Akshat KumarAssistant Professor, School of Information Systems, Singapore ManagementVerified email at smu.edu.sg
Pascal PoupartUniversity of WaterlooVerified email at uwaterloo.ca
Thibaut MunzerInriaVerified email at inria.fr
Nathan RatliffResearch Scientist, Max Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Nikos VlassisSr Data Scientist, NetflixVerified email at netflix.com
Stefan HarmelingProfessor at Heinrich-Heine-Universität DüsseldorfVerified email at hhu.de
Andreas DoerrResearch Scientist, Bosch Center for Artificial Intelligence, Max Planck Institut ISVerified email at tuebingen.mpg.de

Marc Toussaint

Professor of Computer Science, University of Stuttgart, Germany

Verified email at informatik.uni-stuttgart.de - Homepage

Robotics Artificial Intelligence Machine Learning


Title	Cited by	Year
Using machine learning to focus iterative optimization F Agakov, E Bonilla, J Cavazos, B Franke, G Fursin, MFP O'Boyle, ... Proceedings of the international symposium on code generation and …, 2006	416	2006
Robot trajectory optimization using approximate inference M Toussaint Proceedings of the 26th annual international conference on machine learning …, 2009	211	2009
Probabilistic inference for solving discrete and continuous state Markov Decision Processes M Toussaint, A Storkey Proceedings of the 23rd international conference on Machine learning, 945-952, 2006	166	2006
On stochastic optimal control and reinforcement learning by approximate inference K Rawlik, M Toussaint, S Vijayakumar Twenty-Third International Joint Conference on Artificial Intelligence, 2013	149	2013
A no-free-lunch theorem for non-uniform distributions of target functions C Igel, M Toussaint Journal of Mathematical Modelling and Algorithms 3 (4), 313-322, 2005	140	2005
Probabilistic inference as a model of planned behavior. M Toussaint KI 23 (3), 23-29, 2009	120	2009
On classes of functions for which no free lunch results hold C Igel, M Toussaint arXiv preprint cs/0108011, 2001	120	2001
Gaussian process implicit surfaces for shape estimation and grasping S Dragiev, M Toussaint, M Gienger 2011 IEEE International Conference on Robotics and Automation, 2845-2850, 2011	115	2011
Planning as inference M Botvinick, M Toussaint Trends in cognitive sciences 16 (10), 485-488, 2012	111	2012
Multi-class image segmentation using conditional random fields and global classification N Plath, M Toussaint, S Nakajima Proceedings of the 26th Annual International Conference on Machine Learning …, 2009	96	2009
Probabilistic inference for solving (PO) MDPs M Toussaint, S Harmeling, A Storkey University of Edinburgh, School of Informatics Research Report EDI-INF-RR-0934, 2006	91	2006
Exploration in model-based reinforcement learning by empirically estimating learning progress M Lopes, T Lang, M Toussaint, PY Oudeyer Advances in neural information processing systems, 206-214, 2012	87	2012
Planning with noisy probabilistic relational rules T Lang, M Toussaint Journal of Artificial Intelligence Research 39, 1-49, 2010	83	2010
Hierarchical POMDP Controller Optimization by Likelihood Maximization. M Toussaint, L Charlin, P Poupart UAI 24, 562-570, 2008	81	2008
Learning model-free robot control by a Monte Carlo EM algorithm N Vlassis, M Toussaint, G Kontes, S Piperidis Autonomous Robots 27 (2), 123-130, 2009	77	2009
Logic-geometric programming: An optimization-based approach to combined task and motion planning M Toussaint Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015	71	2015
A sensorimotor map: Modulating lateral interactions for anticipation and planning M Toussaint Neural computation 18 (5), 1132-1155, 2006	64	2006
Scalable multiagent planning using probabilistic inference A Kumar, S Zilberstein, M Toussaint Twenty-Second International Joint Conference on Artificial Intelligence, 2011	62	2011
Active learning for teaching a robot grounded relational symbols J Kulick, M Toussaint, T Lang, M Lopes Twenty-Third International Joint Conference on Artificial Intelligence, 2013	61	2013
Integrated motor control, planning, grasping and high-level reasoning in a blocks world using probabilistic inference M Toussaint, N Plath, T Lang, N Jetchev 2010 IEEE International Conference on Robotics and Automation, 385-391, 2010	58	2010

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