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

• Главные авторы: Mario Lovrić (Автор), Tomislav Đuričić (Автор), Han T. N. Tran (Автор), Hussain Hussain (Автор), Emanuel Lacić (Автор), Morten A. Rasmussen (Автор), Roman Kern (Автор)
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• Опубликовано: MDPI AG, 2021-08-01T00:00:00Z.
• Предметы: article
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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...