activity
20162022
most citedLarge-Scale Optical Reservoir Computing for Spatiotemporal Chaotic Systems Prediction

193 citations · 515 across the 8 of their papers we have counts for

collaborators

8 papers

cs.NE2022★ 1 cited

Asymptotic Stability in Reservoir Computing

Jonathan Dong, Erik Börve, Mushegh Rafayelyan +1

Reservoir Computing is a class of Recurrent Neural Networks with internal weights fixed at random. Stability relates to the sensitivity of the network state to perturbations. It is…

cond-mat.dis-nn2021★ 19 cited

Tuneable spin-glass optical simulator based on multiple light scattering

Gianni Jacucci, Louis Delloye, Davide Pierangeli +3

The race to heuristically solve non-deterministic polynomial-time (NP) problems through efficient methods is ongoing. Recently, optics was demonstrated as a promising tool to find…

stat.ML2020★ 12 cited

Reservoir Computing meets Recurrent Kernels and Structured Transforms

Jonathan Dong, Ruben Ohana, Mushegh Rafayelyan +1

Reservoir Computing is a class of simple yet efficient Recurrent Neural Networks where internal weights are fixed at random and only a linear output layer is trained. In the large…

physics.optics2020★ 66 cited

Scalable spin-glass optical simulator

Davide Pierangeli, Mushegh Rafayelyan, Claudio Conti +1

Many developments in science and engineering depend on tackling complex optimizations on large scales. The challenge motivates intense search for specific computing hardware that t…

physics.optics2020★ 193 cited

Large-Scale Optical Reservoir Computing for Spatiotemporal Chaotic Systems Prediction

Mushegh Rafayelyan, Jonathan Dong, Yongqi Tan +2

Reservoir computing is a relatively recent computational paradigm that originates from a recurrent neural network and is known for its wide range of implementations using different…

cs.ET2019★ 127 cited

Optical Reservoir Computing using multiple light scattering for chaotic systems prediction

Jonathan Dong, Mushegh Rafayelyan, Florent Krzakala +1

Reservoir Computing is a relatively recent computational framework based on a large Recurrent Neural Network with fixed weights. Many physical implementations of Reservoir Computin…

physics.optics2017★ 39 cited

Ultra-broadband gradient-pitch Bragg-Berry mirrors

Mushegh Rafayelyan, Gonzague Agez, Etienne Brasselet

The realization of geometric phase optical device operating over a broad spectral range is usually confronted with intrinsic limitations depending of the physical process at play.…

physics.optics2016★ 58 cited

Bragg-Berry mirrors: reflective broadband q-plates

Mushegh Rafayelyan, Etienne Brasselet

We report on the experimental realization of flat mirrors enabling the broadband generation of optical vortices upon reflection. The effect is based on the geometric Berry phase as…