Michiel Hermans
Cited by
Cited by
Training and analysing deep recurrent neural networks
M Hermans, B Schrauwen
Advances in neural information processing systems 26, 2013
A differentiable physics engine for deep learning in robotics
J Degrave, M Hermans, J Dambre
Frontiers in neurorobotics 13, 406386, 2019
Recurrent kernel machines: Computing with infinite echo state networks
M Hermans, B Schrauwen
Neural Computation 24 (1), 104-133, 2012
Memory in linear recurrent neural networks in continuous time
M Hermans, B Schrauwen
Neural Networks 23 (3), 341-355, 2010
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
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), 6729, 2015
Photonic Delay Systems as Machine Learning Implementations
M Hermans, M Soriano, J Dambre, P Bienstman, I Fischer
JMLR 16, 2081-2097, 2015
Memristor models for machine learning
JP Carbajal, J Dambre, M Hermans, B Schrauwen
Neural computation 27 (3), 725-747, 2015
Automated design of complex dynamic systems
M Hermans, B Schrauwen, P Bienstman, J Dambre
PloS one 9 (1), e86696, 2014
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, 21-32, 2016
Embodiment of learning in electro-optical signal processors
M Hermans, P Antonik, M Haelterman, S Massar
Physical review letters 117 (12), 128301, 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
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
M Hermans, B Schrauwen
1st International conference on Robotics in Education (RiE 2010), 49-52, 2010
MACOP modular architecture with control primitives
T Waegeman, M Hermans, B Schrauwen
Frontiers in computational neuroscience 7, 99, 2013
Online training of an opto-electronic reservoir computer
P Antonik, F Duport, A Smerieri, M Hermans, M Haelterman, S Massar
Neural Information Processing: 22nd International Conference, ICONIP 2015 …, 2015
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 Systems …, 2010
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, 1041-1054, 2018
Photonic reservoir computer with output feedback for chaotic time series prediction
P Antonik, M Hermans, M Haelterman, S Massar
2017 International Joint Conference on Neural Networks (IJCNN), 2407-2413, 2017
Toward unified hybrid simulation techniques for spiking neural networks
M D'Haene, M Hermans, B Schrauwen
Neural computation 26 (6), 1055-1079, 2014
The system can't perform the operation now. Try again later.
Articles 1–20