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Should We Embed in Chemistry? A Comparison of Unsupervised Transfer Learning with PCA, UMAP, and VAE on Molecular Fingerprints

Methods for dimensionality reduction are showing significant contributions to knowledge generation in high-dimensional modeling scenarios throughout many disciplines. By achieving a lower dimensional representation (also called embedding), fewer computing resources are needed in downstream machine l...

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Detalles Bibliográficos
Autores principales:	Lovrić, Mario, Đuričić, Tomislav, Tran, Han T. N., Hussain, Hussain, Lacić, Emanuel, Rasmussen, Morten A., Kern, Roman
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2021
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8400160/ https://www.ncbi.nlm.nih.gov/pubmed/34451855 http://dx.doi.org/10.3390/ph14080758

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