Marc Toussaint

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Sethu VijayakumarProfessor of Robotics, University of Edinburgh; Programme Director at The Alan Turing Institute, UKAdresse e-mail validée de ed.ac.uk
Christian IgelDepartment of Computer Science, University of CopenhagenAdresse e-mail validée de diku.dk
Nikolay JetchevSenior Research Scientist at ZalandoAdresse e-mail validée de zalando.de
Manuel LopesInstituto Superior Tecnico, INESC-IDAdresse e-mail validée de tecnico.ulisboa.pt
Danny DriessUniversity of StuttgartAdresse e-mail validée de ipvs.uni-stuttgart.de
Michael GiengerHonda Research Institute EuropeAdresse e-mail validée de honda-ri.de
Peter EnglertUniversity of Southern CaliforniaAdresse e-mail validée de usc.edu
Amos StorkeyProfessor of Machine Learning and AI, School of Informatics, University of Edinburgh, UKAdresse e-mail validée de ed.ac.uk
Stefan SchaalRobotics, Machine Learning, AI, NeuroscienceAdresse e-mail validée de google.com
Ngo Anh VienBosch Center for Artificial Intelligence (BCAI)Adresse e-mail validée de bosch.com
Duy Nguyen-TuongBosch Center for AI, GermanyAdresse e-mail validée de robot-learning.de
Johannes KulickApplied Scientist at Amazon BerlinAdresse e-mail validée de amazon.com
Konrad RawlikPostdoctoral Fellow, Roslin Institute, University of EdinburghAdresse e-mail validée de roslin.ed.ac.uk
Ozgur S. OguzUni Stuttgart & MPI ISAdresse e-mail validée de ipvs.uni-stuttgart.de
Andreas OrtheyMax Planck Institute for Intelligent SystemsAdresse e-mail validée de is.mpg.de
Shlomo ZilbersteinProfessor of Computer Science, University of Massachusetts AmherstAdresse e-mail validée de cs.umass.edu
Jim MainpriceInterim Professor, Stuttgart UniversityAdresse e-mail validée de ipvs.uni-stuttgart.de
Nathan RatliffNVIDIAAdresse e-mail validée de nvidia.com
Akshat KumarAssociate Professor, School of Information Systems, Singapore ManagementAdresse e-mail validée de smu.edu.sg
Robert LieckEPFLAdresse e-mail validée de epfl.ch

Marc Toussaint

Professor of Computer Science, TU Berlin, Germany

Adresse e-mail validée de tu-berlin.de - Page d'accueil

Robotics Robot Learning Artificial Intelligence


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Using machine learning to focus iterative optimization F Agakov, E Bonilla, J Cavazos, B Franke, G Fursin, MFP O'Boyle, ... International Symposium on Code Generation and Optimization (CGO'06), 11 pp.-305, 2006	475	2006
Robot trajectory optimization using approximate inference M Toussaint Proceedings of the 26th annual international conference on machine learning …, 2009	289	2009
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	228	2013
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	218	2006
Planning as inference M Botvinick, M Toussaint Trends in cognitive sciences 16 (10), 485-488, 2012	197	2012
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	156	2005
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	153	2011
Exploration in model-based reinforcement learning by empirically estimating learning progress M Lopes, T Lang, M Toussaint, PY Oudeyer Neural Information Processing Systems (NIPS), 2012	145	2012
Logic-Geometric Programming: An Optimization-Based Approach to Combined Task and Motion Planning. M Toussaint IJCAI, 1930-1936, 2015	135	2015
Probabilistic inference as a model of planned behavior. M Toussaint KI 23 (3), 23-29, 2009	132	2009
Differentiable physics and stable modes for tool-use and manipulation planning MA Toussaint, KR Allen, KA Smith, JB Tenenbaum Robotics: Science and Systems Foundation, 2018	127	2018
On classes of functions for which no free lunch results hold C Igel, M Toussaint arXiv preprint cs/0108011, 2001	127	2001
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	126	2009
Hierarchical POMDP Controller Optimization by Likelihood Maximization. M Toussaint, L Charlin, P Poupart UAI 24, 562-570, 2008	107	2008
Probabilistic inference for solving (PO) MDPs M Toussaint, S Harmeling, A Storkey Technical Report EDI-INF-RR-0934, School of Informatics, University of Edinburgh, 2006	102	2006
Planning with noisy probabilistic relational rules T Lang, M Toussaint Journal of Artificial Intelligence Research 39, 1-49, 2010	89	2010
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	89	2009
Active Learning for Teaching a Robot Grounded Relational Symbols. J Kulick, M Toussaint, T Lang, M Lopes IJCAI, 1451-1457, 2013	79	2013
Scalable multiagent planning using probabilistic inference A Kumar, S Zilberstein, M Toussaint AAAI Press, 2011	72	2011
Fast motion planning from experience: trajectory prediction for speeding up movement generation N Jetchev, M Toussaint Autonomous Robots 34 (1), 111-127, 2013	71	2013

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