Local conformal autoencoder for standardized data coordinates

We propose a local conformal autoencoder (LOCA) for standardized data coordinates. LOCA is a deep learning-based method for obtaining standardized data coordinates from scientific measurements. Data observations are modeled as samples from an unknown, nonlinear deformation of an underlying Riemannia...

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Detalles Bibliográficos
Autores principales: Peterfreund, Erez, Lindenbaum, Ofir, Dietrich, Felix, Bertalan, Tom, Gavish, Matan, Kevrekidis, Ioannis G., Coifman, Ronald R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2020
Materias:
Physical Sciences
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7733838/
https://www.ncbi.nlm.nih.gov/pubmed/33229581
http://dx.doi.org/10.1073/pnas.2014627117

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7733838/
https://www.ncbi.nlm.nih.gov/pubmed/33229581
http://dx.doi.org/10.1073/pnas.2014627117

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