| Theano: A Python framework for fast computation of mathematical expressions R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... arXiv e-prints, arXiv: 1605.02688, 2016 | 765* | 2016 |
| PyBrain T Schaul, J Bayer, D Wierstra, Y Sun, M Felder, F Sehnke, T Rückstieß, ... Journal of Machine Learning Research 11 (ARTICLE), 743-746, 2010 | 422 | 2010 |
| Learning stochastic recurrent networks J Bayer, C Osendorfer arXiv preprint arXiv:1411.7610, 2014 | 189 | 2014 |
| Deep variational bayes filters: Unsupervised learning of state space models from raw data M Karl, M Soelch, J Bayer, P Van der Smagt arXiv preprint arXiv:1605.06432, 2016 | 168 | 2016 |
| Evolving memory cell structures for sequence learning J Bayer, D Wierstra, J Togelius, J Schmidhuber International Conference on Artificial Neural Networks, 755-764, 2009 | 86 | 2009 |
| On Fast Dropout and its Applicability to Recurrent Networks J Bayer, C Osendorfer, N Chen, P van der Smagt preprint arXiv:1311.0701, 2013 | 67 | 2013 |
| Variational inference for on-line anomaly detection in high-dimensional time series M Sölch, J Bayer, M Ludersdorfer, P van der Smagt arXiv preprint arXiv:1602.07109, 2016 | 61 | 2016 |
| Efficient movement representation by embedding dynamic movement primitives in deep autoencoders N Chen, J Bayer, S Urban, P Van Der Smagt 2015 IEEE-RAS 15th international conference on humanoid robots (Humanoids …, 2015 | 35 | 2015 |
| Metrics for deep generative models N Chen, A Klushyn, R Kurle, X Jiang, J Bayer, P Smagt International Conference on Artificial Intelligence and Statistics, 1540-1550, 2018 | 32 | 2018 |
| Continuous robot control using surface electromyography of atrophic muscles J Vogel, J Bayer, P Van Der Smagt 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013 | 30 | 2013 |
| Unsupervised real-time control through variational empowerment M Karl, M Soelch, P Becker-Ehmck, D Benbouzid, P van der Smagt, ... arXiv preprint arXiv:1710.05101, 2017 | 29 | 2017 |
| Harm de Vries, David Warde-Farley, Dustin J R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, and …, 2016 | 27 | 2016 |
| Convolutional neural networks learn compact local image descriptors C Osendorfer, J Bayer, S Urban, P Van Der Smagt International Conference on Neural Information Processing, 624-630, 2013 | 26 | 2013 |
| Learning sequence representations JS Bayer Technische Universität München, 2015 | 17 | 2015 |
| Estimating finger grip force from an image of the hand using convolutional neural networks and gaussian processes N Chen, S Urban, C Osendorfer, J Bayer, P Van Der Smagt 2014 IEEE International Conference on Robotics and Automation (ICRA), 3137-3142, 2014 | 16 | 2014 |
| Computing grip force and torque from finger nail images using gaussian processes S Urban, J Bayer, C Osendorfer, G Westling, BB Edin, P Van Der Smagt 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013 | 14 | 2013 |
| Key insights into hand biomechanics: human grip stiffness can be decoupled from force by cocontraction and predicted from electromyography H Höppner, M Große-Dunker, G Stillfried, J Bayer, P Van Der Smagt Frontiers in neurorobotics 11, 17, 2017 | 13 | 2017 |
| Approximate bayesian inference in spatial environments A Mirchev, B Kayalibay, M Soelch, P van der Smagt, J Bayer arXiv preprint arXiv:1805.07206, 2018 | 10 | 2018 |
| Bayesian Learning of Neural Network Architectures G Dikov, P van der Smagt, J Bayer arXiv preprint arXiv:1901.04436, 2019 | 9 | 2019 |
| Training Neural Networks with Implicit Variance J Bayer, C Osendorfer, S Urban, P van der Smagt International Conference on Neural Information Processing Systems, 2013 | 9 | 2013 |
Patrick van der SmagtAdresse e-mail validée de tum.de
