179 citations · 596 across the 9 of their papers we have counts for
7 papers · 1 filter
Random pattern and frequency generation using a photonic reservoir computer with output feedback
Piotr Antonik, Michiel Hermans, Marc Haelterman +1
Reservoir computing is a bio-inspired computing paradigm for processing time dependent signals. The performance of its analogue implementations matches other digital algorithms on…
Online training for high-performance analogue readout layers in photonic reservoir computers
Piotr Antonik, Marc Haelterman, Serge Massar
Introduction. Reservoir Computing is a bio-inspired computing paradigm for processing time-dependent signals. The performance of its hardware implementation is comparable to state-…
Human action recognition with a large-scale brain-inspired photonic computer
Piotr Antonik, Nicolas Marsal, Daniel Brunner +1
The recognition of human actions in video streams is a challenging task in computer vision, with cardinal applications in e.g. brain-computer interface and surveillance. Deep learn…
Large-scale spatiotemporal photonic reservoir computer for image classification
Piotr Antonik, Nicolas Marsal, Damien Rontani
We propose a scalable photonic architecture for implementation of feedforward and recurrent neural networks to perform the classification of handwritten digits from the MNIST datab…
Bayesian optimisation of large-scale photonic reservoir computers
Piotr Antonik, Nicolas Marsal, Daniel Brunner +1
Introduction. Reservoir computing is a growing paradigm for simplified training of recurrent neural networks, with a high potential for hardware implementations. Numerous experimen…
Brain-inspired photonic signal processor for periodic pattern generation and chaotic system emulation
Piotr Antonik, Marc Haelterman, Serge Massar
Reservoir computing is a bio-inspired computing paradigm for processing time-dependent signals. Its hardware implementations have received much attention because of their simplicit…