407 citations · 966 across the 11 of their papers we have counts for
12 papers
Fast Autofocusing using Tiny Transformer Networks for Digital Holographic Microscopy
Stéphane Cuenat, Louis Andréoli, Antoine N. André +4
The numerical wavefront backpropagation principle of digital holography confers unique extended focus capabilities, without mechanical displacements along z-axis. However, the dete…
Boolean learning under noise-perturbations in hardware neural networks
Louis Andreoli, Xavier Porte, Stéphane Chrétien +3
A high efficiency hardware integration of neural networks benefits from realizing nonlinearity, network connectivity and learning fully in a physical substrate. Multiple systems ha…
Three dimensional waveguide-interconnects for scalable integration of photonic neural networks
Johnny Moughames, Xavier Porte, Michael Thiel +5
Photonic waveguides are prime candidates for integrated and parallel photonic interconnects. Such interconnects correspond to large-scale vector matrix products, which are at the h…
Advancing Fourier: space-time concepts in ultrafast optics, imaging and photonic neural networks
Luc Froehly, Francois Courvoisier, Daniel Brunner +5
The concepts of Fourier optics were established in France in the 1940s by Pierre-Michel Duffieux, and laid the foundations of an extensive series of activities in the French resear…
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…
Reinforcement Learning in a large scale photonic Recurrent Neural Network
Julian Bueno, Sheler Maktoobi, Luc Froehly +4
Photonic Neural Network implementations have been gaining considerable attention as a potentially disruptive future technology. Demonstrating learning in large scale neural network…
Single shot ultrafast laser processing of high-aspect ratio nanochannels using elliptical Bessel beams
R. Meyer, M. Jacquot, R. Giust +6
Ultrafast lasers have revolutionized material processing, opening a wealth of new applications in many areas of science. A recent technology that allows the cleaving of transparent…
Barium fluoride whispering-gallery-mode disk-resonator with one billion quality-factor
Guoping Lin, Souleymane Diallo, Rémi Henriet +2
We demonstrate a monolithic optical whispering gallery mode resonator fabricated with barium fluoride (BaF) with an ultra-high quality () factor above at nm, a…
Sending femtosecond pulses in circles: highly non-paraxial accelerating beams
F. Courvoisier, A. Mathis, L. Froehly +5
We use caustic beam shaping on 100 fs pulses to experimentally generate non-paraxial accelerating beams along a 60 degree circular arc, moving laterally by 14 \mum over a 28 \mum p…