Nonlinear dimensionality reduction for low data regimes in photonics design

From National Research Council Canada

DOIResolve DOI: https://doi.org/10.1109/PN56061.2022.9908251
AuthorSearch for: 1; Search for: 1; Search for: 2; Search for: 2; Search for: 2; Search for: 2; Search for: 2; Search for: 2
Affiliation
  1. National Research Council of Canada. Digital Technologies
  2. National Research Council of Canada. Advanced Electronics and Photonics
FunderSearch for: National Research Council of Canada
FormatText, Article
Conference2022 Photonics North (PN), May 24-26, 2022, Niagara Falls, Ontario, Canada
Subjectdimensionality reduction; autoencoder; small data; nanophotonic design; silicon photonics; machine learning; dimensionality reduction; neural networks; photonics; principal component analysis
Abstract
Publication date
PublisherIEEE
In
LanguageEnglish
Peer reviewedYes
Export citationExport as RIS
Report a correctionReport a correction (opens in a new tab)
Record identifierc548520b-92e2-48da-af32-fc26a9d79d1c
Record created2022-10-25
Record modified2023-03-16
Date modified: