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 | 263 | 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 | 100 | 2014 |
Unsupervised Learning of Local Features for Music Classification. J Wülfing, MA Riedmiller ISMIR, 139-144, 2012 | 58 | 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 |
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 | | |