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Sebastian Urban
Sebastian Urban
surban.net
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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
1114*2016
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
892013
Optical pufs reloaded
U Rührmair, C Hilgers, S Urban, A Weiershäuser, E Dinter, B Forster, ...
Cryptology ePrint Archive, 2013
882013
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
592015
Convolutional neural networks learn compact local image descriptors
C Osendorfer, J Bayer, S Urban, P van der Smagt
Neural Information Processing: 20th International Conference, ICONIP 2013 …, 2013
312013
Sensor calibration and hysteresis compensation with heteroscedastic gaussian processes
S Urban, M Ludersdorfer, P Van Der Smagt
IEEE Sensors Journal 15 (11), 6498-6506, 2015
252015
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
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
192014
Snookie: An autonomous underwater vehicle with artificial lateral-line system
AN Vollmayr, S Sosnowski, S Urban, S Hirche, JL van Hemmen
Flow Sensing in Air and Water: Behavioral, Neural and Engineering Principles …, 2014
152014
Neural Network Architectures and Activation Functions: A Gaussian Process Approach
S Urban
Technical University Munich, 2018
122018
A neural transfer function for a smooth and differentiable transition between additive and multiplicative interactions
S Urban, P van der Smagt
arXiv preprint arXiv:1503.05724, 2015
112015
Supervised spike-timing-dependent plasticity: A spatiotemporal neuronal learning rule for function approximation and decisions
JMP Franosch, S Urban, JL van Hemmen
Neural computation 25 (12), 3113-3130, 2013
112013
Revisiting Optical Physical Unclonable Functions.
U Rührmair, C Hilgers, S Urban, A Weiershäuser, E Dinter, B Forster, ...
IACR Cryptol. ePrint Arch. 2013, 215, 2013
112013
Training neural networks with implicit variance
J Bayer, C Osendorfer, S Urban, P van der Smagt
Neural Information Processing: 20th International Conference, ICONIP 2013 …, 2013
102013
Measuring fingertip forces from camera images for random finger poses
N Chen, S Urban, J Bayer, P van der Smagt
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015
92015
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
72013
climin-A pythonic framework for gradient-based function optimization
J Bayer, C Osendorfer, S Diot-Girard, T Rueckstiess, S Urban
TUM, Tech. Rep., 2015
62015
Gaussian process neurons learn stochastic activation functions
S Urban, M Basalla, P van der Smagt
arXiv preprint arXiv:1711.11059, 2017
52017
Automatic differentiation for tensor algebras
S Urban, P van der Smagt
arXiv preprint arXiv:1711.01348, 2017
22017
A Differentiable Transition Between Additive and Multiplicative Neurons
W Köpp, P van der Smagt, S Urban
arXiv preprint arXiv:1604.03736, 2016
22016
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