Jan Manuel Wülfing

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Martin RiedmillerDeepMindVerified email at google.com
Joschka BoedeckerProfessor of Computer Science, University of Freiburg, GermanyVerified email at informatik.uni-freiburg.de
Manuel BlumUniversity of FreiburgVerified email at informatik.uni-freiburg.de
Ulrich EgertUniv. FreiburgVerified email at imtek.uni-freiburg.de
Sreedhar S KumarETH ZürichVerified email at bsse.ethz.ch
Samora OkujeniBiomicrotechnology, Dept. for Microsystems Engineering, University FreiburgVerified email at biologie.uni-freiburg.de
Joachim HertzbergUniversity of Osnabrück and DFKI, OsnabrückVerified email at uos.de
Thomas WiemannProfessor of Robotics in Computer Science at Fulda University of Applied SciencesVerified email at informatik.hs-fulda.de
Andreas NüchterProfessor of Computer Science (Robotics), University of Würzburg, GermanyVerified email at nuechti.de
Kai LingemannDFKIVerified email at dfki.de
Stefan StieneUniversity of Applied Sciences OsnabrückVerified email at dfki.de
Jost Tobias SpringenbergGoogle DeepMind

Jan Manuel Wülfing

DB InfraGO

Verified email at deutschebahn.com

Machine Learning Reinforcement Learning Deep Learning


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A learned feature descriptor for object recognition in RGB-D data M Blum, JT Springenberg, J Wülfing, M Riedmiller 2012 IEEE international conference on robotics and automation, 1298-1303, 2012	266	2012
Approximate real-time optimal control based on sparse gaussian process models J Boedecker, JT Springenberg, J Wülfing, M Riedmiller 2014 IEEE symposium on adaptive dynamic programming and reinforcement …, 2014	104	2014
Unsupervised Learning of Local Features for Music Classification. J Wülfing, MA Riedmiller ISMIR, 139-144, 2012	60	2012
Autonomous optimization of targeted stimulation of neuronal networks SS Kumar, J Wülfing, S Okujeni, J Boedecker, M Riedmiller, U Egert PLoS computational biology 12 (8), e1005054, 2016	21	2016
Adaptive long-term control of biological neural networks with deep reinforcement learning JM Wülfing, SS Kumar, J Boedecker, M Riedmiller, U Egert Neurocomputing 342, 66-74, 2019	14	2019
Towards real time robot 6d localization in a polygonal indoor map based on 3d tof camera data J Wülfing, J Hertzberg, K Lingemann, A Nüchter, T Wiemann, S Stiene IFAC Proceedings Volumes 43 (16), 91-96, 2010	13	2010
On the applicability of unsupervised feature learning for object recognition in rgb-d data M Blum, JT Springenberg, J Wülfing, M Riedmiller NIPS Workshop on Deep Learning and Unsupervised Feature Learning, 2011	9	2011
Controlling biological neural networks with deep reinforcement learning. J Wülfing, SS Kumar, J Boedecker, MA Riedmiller, U Egert ESANN, 2018	2	2018
Autonomous control of network activity SS Kumar, J Wülfing, J Boedecker, R Wimmer, M Riedmiller, B Becker, ... Proc. of the 9th Int’l Meeting on Substrate-Integrated Microelectrode Arrays …, 2014	1	2014
Intelligent Railway Capacity and Traffic Management Using Multi-Agent Deep Reinforcement Learning S Schneider, A Roets, C Stirbu, F Safaei, F Ghriss, J Wülfing, M Güral, ...		2024
Stable deep reinforcement learning J Wülfing Dissertation, Universität Freiburg, 2019, 2019		2019
Autonomous optimization of targeted stimulation of neuronal networks U Egert, M Riedmiller, J Boedecker, J Wülfing, S Saseendran Kumar, ...		2016
A Machine Learning Based Approach to Control Network Activity SS Kumar, J Wülfing, S Okujeni, J Boedecker, M Riedmiller, U Egert

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