Most of the time, I do machine learning. Currently, I am pursuing a doctorate at the Technische Unversitaet Muenchen as a member of the chair for robotics and embedded systems, part of the department for informatics. I am part of the group for biomimetic robots and machine learning.
From time to time, I freelance. My specialities are sequential and time series data, visualizations and deep learning. I have worked in brain computer interfaces, biological signals, energy consumption and more areas.
The best way to reach me is via mail: email@example.com.
Some articles came out of the scientific work I do. They are listed below.
- Training Neural Networks with Implicit Variance (Bayer, Justin; Osendorfer, Christian; Urban, Sebastian; van der Smagt, Patrick) International Conference on Neural Information Processing Systems, 2013.
- Convolutional Neural Networks learn compact local image descriptors (Osendorfer, C., Bayer, J., & van der Smagt, P.) arXiv preprint arXiv:1304.7948
- Unsupervised Feature Learning for local image descriptors (Osendorfer, C., Bayer, J., & van der Smagt, P.) arXiv preprint arXiv:1301.2840
- Learning sequence neighbourhood metrics (Bayer, J., Osendorfer, C., & van der Smagt, P. ) Artificial Neural Networks and Machine Learning–ICANN 2012 (pp. 531-538). Springer Berlin Heidelberg.
- Identification of human limb stiffness in 5 DoF and estimation via EMG. (Lakatos, D., Rüschen, D., Bayer, J., Vogel, J., & van der Smagt, P.) 13th International Symposium on Experimental Robotics June 17-21, 2012
- PyBrain (Schaul, T., Bayer, J., Wierstra, D., Sun, Y., Felder, M., Sehnke, F., ... & Schmidhuber, J.) The Journal of Machine Learning Research, 11, 743-746.
- Evolving memory cell structures for sequence learning (Bayer, J., Wierstra, D., Togelius, J., & Schmidhuber, J. ) In Artificial Neural Networks–ICANN 2009 (pp. 755-764). Springer Berlin Heidelberg.
Python and 0MQ do scale to
real timereally fast robot control at the Munich data geek meetup, august edition.