128 citations · 509 across the 22 of their papers we have counts for
4 papers · 1 filter
Reservoir-size dependent learning in analogue neural networks
Xavier Porte, Louis Andreoli, Maxime Jacquot +2
The implementation of artificial neural networks in hardware substrates is a major interdisciplinary enterprise. Well suited candidates for physical implementations must combine no…
Fundamental aspects of noise in analog-hardware neural networks
Nadezhda Semenova, Xavier Porte, Louis Andreoli +3
We study and analyze the fundamental aspects of noise propagation in recurrent as well as deep, multi-layer networks. The main focus of our study are neural networks in analogue ha…
Diffractive coupling for photonic networks: how big can we go?
Sheler Maktoobi, Luc Froehly, Louis Andreoli +4
Photonic networks are considered a promising substrate for high-performance future computing systems. Compared to electronics, photonics has significant advantages for a fully para…
Coupled nonlinear delay systems as deep convolutional neural networks
Bogdan Penkovsky, Xavier Porte, Maxime Jacquot +2
Neural networks are currently transforming the field of computer algorithms, yet their emulation on current computing substrates is highly inefficient. Reservoir computing was succ…