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20082023
most citedReinforcement Learning in a large scale photonic Recurrent Neural Network

407 citations · 1.7k across the 34 of their papers we have counts for

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Showing 2020Show all

8 papers · 1 filter

cs.NE2020

A complete, parallel and autonomous photonic neural network in a semiconductor multimode laser

Xavier Porte, Anas Skalli, Nasibeh Haghighi +3

Neural networks are one of the disruptive computing concepts of our time. However, they fundamentally differ from classical, algorithmic computing in a number of fundamental aspect…

cs.ET2020★ 23 cited

Optical Neural Networks: The 3D connection

Niyazi Ulas Dinc, Demetri Psaltis, Daniel Brunner

We motivate a new canonical strategy for integrating photonic neural networks (NNs) by leveraging 3D printing. Our believe is that a NN's parallel and dense connectivity is not sca…

cs.ET2020★ 41 cited

Developing of a photonic hardware platform for brain-inspired computing based on VCSEL arrays

T. Heuser, M. Pflüger, I. Fischer +3

Brain-inspired computing concepts like artificial neural networks have become promising alternatives to classical von Neumann computer architectures. Photonic neural networks targe…

cs.NE2020★ 179 cited

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…

cs.NE2020

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…

physics.optics2020★ 75 cited

Noise-enhanced spatial-photonic Ising machine

Davide Pierangeli, Giulia Marcucci, Daniel Brunner +1

Ising machines are novel computing devices for the energy minimization of Ising models. These combinatorial optimization problems are of paramount importance for science and techno…