Publication

Machine learning with multimode fibers

Demetri Psaltis, Christophe Moser, Ilker Oguz, Ugur Tegin, Mustafa Yildirim
2021
Conference Papers

Abstract

A novel optical computing framework by harnessing spatiotemporal nonlinear effects of multimode fibers for machine learning is presented. With linear and nonlinear interactions of the spatial fiber modes, a brain-inspired computation engine is experimentally realized.

Official source

https://infoscience.epfl.ch/entities/publication/3b8b84fe-735c-45d3-a0b0-efd9bc3ed495

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Machine learning with multimode fibers

Chat with Graph Search

Exploiting Representation Similarities in Self-Supervised Learning for Vision Tasks

Modelleyen: Continual Learning and Planning via Structured Modelling of Environment Dynamics

LIONHEART: A Layer-based Mapping Framework for Heterogeneous Systems with Analog In-Memory Computing Tiles