Christian Osendorfer (Dr.)
Christian Osendorfer (Dr.)
former TU München
Verified email at in.tum.de - Homepage
TitleCited byYear
Parameter-exploring policy gradients
F Sehnke, C Osendorfer, T Rückstieß, A Graves, J Peters, J Schmidhuber
Neural Networks 23 (4), 551-559, 2010
1802010
Learning stochastic recurrent networks
J Bayer, C Osendorfer
arXiv preprint arXiv:1411.7610, 2014
1302014
Image super-resolution with fast approximate convolutional sparse coding
C Osendorfer, H Soyer, P Van Der Smagt
International Conference on Neural Information Processing, 250-257, 2014
622014
Policy gradients with parameter-based exploration for control
F Sehnke, C Osendorfer, T Rückstieß, A Graves, J Peters, J Schmidhuber
International Conference on Artificial Neural Networks, 387-396, 2008
612008
On fast dropout and its applicability to recurrent networks
J Bayer, C Osendorfer, D Korhammer, N Chen, S Urban, P van der Smagt
arXiv preprint arXiv:1311.0701, 2013
592013
Music similarity estimation with the mean-covariance restricted Boltzmann machine
J Schluter, C Osendorfer
2011 10th International Conference on Machine Learning and Applications and …, 2011
372011
Sequential feature selection for classification
T Rückstieß, C Osendorfer, P van der Smagt
Australasian Joint Conference on Artificial Intelligence, 132-141, 2011
372011
Using tactile sensation for learning contact knowledge: Discriminate collision from physical interaction
S Golz, C Osendorfer, S Haddadin
2015 IEEE International Conference on Robotics and Automation (ICRA), 3788-3794, 2015
312015
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
242013
Minimizing data consumption with sequential online feature selection
T Rückstieß, C Osendorfer, P van der Smagt
International Journal of Machine Learning and Cybernetics 4 (3), 235-243, 2013
202013
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
162014
NAIS-Net: stable deep networks from non-autonomous differential equations
M Ciccone, M Gallieri, J Masci, C Osendorfer, F Gomez
Advances in Neural Information Processing Systems, 3025-3035, 2018
152018
Multimodal parameter-exploring policy gradients
F Sehnke, A Graves, C Osendorfer, J Schmidhuber
2010 Ninth International Conference on Machine Learning and Applications …, 2010
152010
Model-free robot anomaly detection
R Hornung, H Urbanek, J Klodmann, C Osendorfer, P Van Der Smagt
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2014
142014
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
142013
Policy gradients for cryptanalysis
F Sehnke, C Osendorfer, J Sölter, J Schmidhuber, U Rührmair
International Conference on Artificial Neural Networks, 168-177, 2010
102010
Training neural networks with implicit variance
J Bayer, C Osendorfer, S Urban, P van der Smagt
International Conference on Neural Information Processing, 132-139, 2013
82013
Learning sequence neighbourhood metrics
J Bayer, C Osendorfer, P Van Der Smagt
International Conference on Artificial Neural Networks, 531-538, 2012
82012
Unsupervised feature learning for low-level local image descriptors
C Osendorfer, J Bayer, S Urban, P Van Der Smagt
arXiv preprint arXiv:1301.2840, 2013
62013
ViSMI: Software distributed shared memory for infiniband clusters
C Osendorfer, C Trinitis, M Mairandres, J Tao
Third IEEE International Symposium on Network Computing and Applications …, 2004
62004
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