Characterizing Uncertainty in Machine Learning for Chemistry-Reference-Cited by-同舟云学术

Characterizing Uncertainty in Machine Learning for Chemistry

Published:2023-06-20 Issue:13 Volume:63 Page:4012-4029
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Heid Esther¹²^ORCID,McGill Charles J.¹³^ORCID,Vermeire Florence H.¹⁴,Green William H.¹^ORCID

Affiliation:

1. Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States

2. Institute of Materials Chemistry, TU Wien, 1060 Vienna, Austria

3. Department of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, Virginia 23284, United States

4. Department of Chemical Engineering, KU Leuven, Celestijnenlaan 200F, B-3001 Leuven, Belgium

Funder

Austrian Science Fund

Machine Learning for Pharmaceutical Discovery and Synthesis Consortium

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.3c00373

Reference96 articles.

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5. ToxicBlend: Virtual screening of toxic compounds with ensemble predictors

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