Michiel Hermans

Publication Activity (10 Years)

Years Active: 2010-2020
Publications (10 Years): 18

Top Topics

Online Training

Backpropagation Algorithm

Top Venues

IEEE Trans. Neural Networks Learn. Syst.

Publications

Piotr Antonik, Michiel Hermans, Marc Haelterman, Serge Massar
Random pattern and frequency generation using a photonic reservoir computer with output feedback. CoRR (2020)
Jonas Degrave, Michiel Hermans, Joni Dambre, Francis Wyffels
A Differentiable Physics Engine for Deep Learning in Robotics. Frontiers Neurorobotics 13 (2019)
Piotr Antonik, Michiel Hermans, Marc Haelterman, Serge Massar
Random Pattern and Frequency Generation Using a Photonic Reservoir Computer with Output Feedback. Neural Process. Lett. 47 (3) (2018)
Jonas Degrave, Michiel Hermans, Joni Dambre, Francis Wyffels
A Differentiable Physics Engine for Deep Learning in Robotics. ICLR (Workshop) (2017)
Piotr Antonik, Michiel Hermans, Marc Haelterman, Serge Massar
Photonic reservoir computer with output feedback for chaotic time series prediction. IJCNN (2017)
Piotr Antonik, Michiel Hermans, Marc Haelterman, Serge Massar
Chaotic Time Series Prediction Using a Photonic Reservoir Computer with Output Feedback. AAAI (2017)
Piotr Antonik, François Duport, Michiel Hermans, Anteo Smerieri, Marc Haelterman, Serge Massar
Online Training of an Opto-Electronic Reservoir Computer Applied to Real-Time Channel Equalization. IEEE Trans. Neural Networks Learn. Syst. 28 (11) (2017)
Michiel Hermans, Piotr Antonik, Marc Haelterman, Serge Massar
Embodiment of Learning in Electro-Optical Signal Processors. CoRR (2016)
Piotr Antonik, François Duport, Michiel Hermans, Anteo Smerieri, Marc Haelterman, Serge Massar
Online Training of an Opto-Electronic Reservoir Computer Applied to Real-Time Channel Equalisation. CoRR (2016)
Piotr Antonik, Michiel Hermans, Marc Haelterman, Serge Massar
Pattern and Frequency Generation Using an Opto-Electronic Reservoir Computer with Output Feedback. ICONIP (2) (2016)
Piotr Antonik, Michiel Hermans, Marc Haelterman, Serge Massar
Towards Adjustable Signal Generation with Photonic Reservoir Computers. ICANN (1) (2016)
Jonas Degrave, Michiel Hermans, Joni Dambre, Francis Wyffels
A Differentiable Physics Engine for Deep Learning in Robotics. CoRR (2016)
Michiel Hermans, Miguel C. Soriano, Joni Dambre, Peter Bienstman, Ingo Fischer
Photonic Delay Systems as Machine Learning Implementations. CoRR (2015)
Michiel Hermans, Miguel C. Soriano, Joni Dambre, Peter Bienstman, Ingo Fischer
Photonic delay systems as machine learning implementations. J. Mach. Learn. Res. 16 (2015)
Michiel Hermans, Thomas Van Vaerenbergh
Towards Trainable Media: Using Waves for Neural Network-Style Training. CoRR (2015)
Michiel Hermans, Joni Dambre, Peter Bienstman
Optoelectronic Systems Trained With Backpropagation Through Time. IEEE Trans. Neural Networks Learn. Syst. 26 (7) (2015)
Juan Pablo Carbajal, Joni Dambre, Michiel Hermans, Benjamin Schrauwen
Memristor Models for Machine Learning. Neural Comput. 27 (3) (2015)
Piotr Antonik, François Duport, Anteo Smerieri, Michiel Hermans, Marc Haelterman, Serge Massar
Online Training of an Opto-Electronic Reservoir Computer. ICONIP (2) (2015)
Michiel Hermans, Michael Burm, Joni Dambre, Peter Bienstman
Trainable and Dynamic Computing: Error Backpropagation through Physical Media. CoRR (2014)
Michiel D'Haene, Michiel Hermans, Benjamin Schrauwen
Toward Unified Hybrid Simulation Techniques for Spiking Neural Networks. Neural Comput. 26 (6) (2014)
Juan Pablo Carbajal, Joni Dambre, Michiel Hermans, Benjamin Schrauwen
Memristor models for machine learning. CoRR (2014)
Michiel Hermans, Benjamin Schrauwen
Training and Analysing Deep Recurrent Neural Networks. NIPS (2013)
Tim Waegeman, Michiel Hermans, Benjamin Schrauwen
MACOP modular architecture with control primitives. Frontiers Comput. Neurosci. 7 (2013)
Michiel Hermans, Benjamin Schrauwen
Recurrent Kernel Machines: Computing with Infinite Echo State Networks. Neural Comput. 24 (1) (2012)
Michiel Hermans, Benjamin Schrauwen
Infinite Sparse Threshold Unit Networks. ICANN (1) (2012)
Michiel Hermans, Benjamin Schrauwen
Memory in linear recurrent neural networks in continuous time. Neural Networks 23 (3) (2010)
Michiel Hermans, Benjamin Schrauwen
Memory in reservoirs for high dimensional input. IJCNN (2010)
Michiel Hermans, Benjamin Schrauwen
One step Backpropagation Through Time for learning input mapping in reservoir computing applied to speech recognition. ISCAS (2010)