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

Internet

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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