Michiel Hermans
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Training and analysing deep recurrent neural networks
M Hermans, B Schrauwen
Advances in neural information processing systems 26, 190-198, 2013
Recurrent kernel machines: Computing with infinite echo state networks
M Hermans, B Schrauwen
Neural Computation 24 (1), 104-133, 2012
A differentiable physics engine for deep learning in robotics
J Degrave, M Hermans, J Dambre
Frontiers in neurorobotics 13, 6, 2019
Memory in linear recurrent neural networks in continuous time
M Hermans, B Schrauwen
Neural Networks 23 (3), 341-355, 2010
Photonic Delay Systems as Machine Learning Implementations
M Hermans, M Soriano, J Dambre, P Bienstman, I Fischer
JMLR 16, 2081-2097, 2015
Trainable hardware for dynamical computing using error backpropagation through physical media
M Hermans, M Burm, T Van Vaerenbergh, J Dambre, P Bienstman
Nature communications 6 (1), 1-8, 2015
Online training of an opto-electronic reservoir computer applied to real-time channel equalization
P Antonik, F Duport, M Hermans, A Smerieri, M Haelterman, S Massar
IEEE transactions on neural networks and learning systems 28 (11), 2686-2698, 2016
Automated design of complex dynamic systems
M Hermans, B Schrauwen, P Bienstman, J Dambre
PloS one 9 (1), e86696, 2014
Memristor models for machine learning
JP Carbajal, J Dambre, M Hermans, B Schrauwen
Neural computation 27 (3), 725-747, 2015
Towards pattern generation and chaotic series prediction with photonic reservoir computers
P Antonik, M Hermans, F Duport, M Haelterman, S Massar
Real-time Measurements, Rogue Events, and Emerging Applications 9732, 97320B, 2016
Optoelectronic systems trained with backpropagation through time
M Hermans, J Dambre, P Bienstman
IEEE Transactions on Neural Networks and Learning Systems 26 (7), 1545-1550, 2014
Embodiment of learning in electro-optical signal processors
M Hermans, P Antonik, M Haelterman, S Massar
Physical review letters 117 (12), 128301, 2016
Online training of an opto-electronic reservoir computer
P Antonik, F Duport, A Smerieri, M Hermans, M Haelterman, S Massar
International Conference on Neural Information Processing, 233-240, 2015
MACOP modular architecture with control primitives
TW Waegeman, M Hermans, B Schrauwen
Frontiers in computational neuroscience 7, 99, 2013
Memory in reservoirs for high dimensional input
M Hermans, B Schrauwen
The 2010 International Joint Conference on Neural Networks (IJCNN), 1-7, 2010
Building robots as a tool to motivate students into an engineering education
F Wyffels, M Hermans, B Schrauwen
AT&P JOURNAL PLUS 2 (2010-2), 113-116, 2010
One step backpropagation through time for learning input mapping in reservoir computing applied to speech recognition
M Hermans, B Schrauwen
Proceedings of 2010 IEEE International Symposium on Circuits and Systemsá…, 2010
Determinants Of The Gold Price
B Dierinck, M Fr÷mmel, B Schrauwen, M Hermans
Unievrsiteit Gent, 2012
Random pattern and frequency generation using a photonic reservoir computer with output feedback
P Antonik, M Hermans, M Haelterman, S Massar
Neural Processing Letters 47 (3), 1041-1054, 2018
Towards adjustable signal generation with photonic reservoir computers
P Antonik, M Hermans, M Haelterman, S Massar
International Conference on Artificial Neural Networks, 374-381, 2016
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