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ORCIDMichiel Hermans
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2020 – today
- 2020
[i8]Piotr Antonik, Michiel Hermans, Marc Haelterman, Serge Massar:
Random pattern and frequency generation using a photonic reservoir computer with output feedback. CoRR abs/2012.10615 (2020)
2010 – 2019
- 2019
- [j10]Jonas Degrave, Michiel Hermans, Joni Dambre
, Francis Wyffels:
A Differentiable Physics Engine for Deep Learning in Robotics. Frontiers Neurorobotics 13: 6 (2019) - 2018
- [j9]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): 1041-1054 (2018) - 2017
- [j8]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): 2686-2698 (2017) - [c10]Piotr Antonik, Michiel Hermans, Marc Haelterman, Serge Massar:
Chaotic Time Series Prediction Using a Photonic Reservoir Computer with Output Feedback. AAAI 2017: 4901-4902 - [c9]Jonas Degrave, Michiel Hermans, Joni Dambre, Francis Wyffels:
A Differentiable Physics Engine for Deep Learning in Robotics. ICLR (Workshop) 2017 - [c8]Piotr Antonik, Michiel Hermans, Marc Haelterman, Serge Massar:
Photonic reservoir computer with output feedback for chaotic time series prediction. IJCNN 2017: 2407-2413 - 2016
- [c7]Piotr Antonik, Michiel Hermans, Marc Haelterman, Serge Massar:
Towards Adjustable Signal Generation with Photonic Reservoir Computers. ICANN (1) 2016: 374-381 - [c6]Piotr Antonik, Michiel Hermans, Marc Haelterman, Serge Massar:
Pattern and Frequency Generation Using an Opto-Electronic Reservoir Computer with Output Feedback. ICONIP (2) 2016: 318-325 - [i7]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 abs/1610.06268 (2016) - [i6]Michiel Hermans, Piotr Antonik, Marc Haelterman, Serge Massar:
Embodiment of Learning in Electro-Optical Signal Processors. CoRR abs/1610.06269 (2016) - [i5]Jonas Degrave, Michiel Hermans, Joni Dambre, Francis Wyffels:
A Differentiable Physics Engine for Deep Learning in Robotics. CoRR abs/1611.01652 (2016) - 2015
- [j7]Michiel Hermans, Miguel C. Soriano, Joni Dambre, Peter Bienstman, Ingo Fischer:
Photonic delay systems as machine learning implementations. J. Mach. Learn. Res. 16: 2081-2097 (2015) - [j6]Juan Pablo Carbajal, Joni Dambre, Michiel Hermans, Benjamin Schrauwen:
Memristor Models for Machine Learning. Neural Comput. 27(3): 725-747 (2015) - [j5]Michiel Hermans, Joni Dambre, Peter Bienstman:
Optoelectronic Systems Trained With Backpropagation Through Time. IEEE Trans. Neural Networks Learn. Syst. 26(7): 1545-1550 (2015) - [c5]Piotr Antonik, François Duport, Anteo Smerieri, Michiel Hermans, Marc Haelterman, Serge Massar:
Online Training of an Opto-Electronic Reservoir Computer. ICONIP (2) 2015: 233-240 - [i4]Michiel Hermans, Miguel C. Soriano, Joni Dambre, Peter Bienstman, Ingo Fischer:
Photonic Delay Systems as Machine Learning Implementations. CoRR abs/1501.02592 (2015) - [i3]Michiel Hermans, Thomas Van Vaerenbergh:
Towards Trainable Media: Using Waves for Neural Network-Style Training. CoRR abs/1510.03776 (2015) - 2014
- [j4]Michiel D'Haene, Michiel Hermans, Benjamin Schrauwen:
Toward Unified Hybrid Simulation Techniques for Spiking Neural Networks. Neural Comput. 26(6): 1055-1079 (2014) - [i2]Juan Pablo Carbajal, Joni Dambre, Michiel Hermans, Benjamin Schrauwen:
Memristor models for machine learning. CoRR abs/1406.2210 (2014) - [i1]Michiel Hermans, Michael Burm, Joni Dambre, Peter Bienstman:
Trainable and Dynamic Computing: Error Backpropagation through Physical Media. CoRR abs/1407.6637 (2014) - 2013
- [j3]Tim Waegeman, Michiel Hermans, Benjamin Schrauwen:
MACOP modular architecture with control primitives. Frontiers Comput. Neurosci. 7: 99 (2013) - [c4]Michiel Hermans, Benjamin Schrauwen:
Training and Analysing Deep Recurrent Neural Networks. NIPS 2013: 190-198 - 2012
- [j2]Michiel Hermans, Benjamin Schrauwen:
Recurrent Kernel Machines: Computing with Infinite Echo State Networks. Neural Comput. 24(1): 104-133 (2012) - [c3]Michiel Hermans, Benjamin Schrauwen:
Infinite Sparse Threshold Unit Networks. ICANN (1) 2012: 612-619 - 2010
- [j1]Michiel Hermans, Benjamin Schrauwen:
Memory in linear recurrent neural networks in continuous time. Neural Networks 23(3): 341-355 (2010) - [c2]Michiel Hermans, Benjamin Schrauwen:
Memory in reservoirs for high dimensional input. IJCNN 2010: 1-7 - [c1]Michiel Hermans, Benjamin Schrauwen:
One step Backpropagation Through Time for learning input mapping in reservoir computing applied to speech recognition. ISCAS 2010: 521-524
Coauthor Index
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