Interpretable machine learning as a tool for scientific discovery in chemistry-Reference-Cited by-同舟云学术

Interpretable machine learning as a tool for scientific discovery in chemistry

Published:2020 Issue:48 Volume:44 Page:20914-20920
ISSN:1144-0546
Container-title:New Journal of Chemistry
language:en
Short-container-title:New J. Chem.

Author:

Dybowski Richard¹²³^ORCID

Affiliation:

1. St John's College, University of Cambridge

2. Cambridge CB2 1TP

3. UK

Abstract

There has been an upsurge of interest in applying machine learning to chemistry, and impressive predictive accuracies have been achieved, but this has been done without providing any insight into what has been learnt from the training data.

Publisher

Royal Society of Chemistry (RSC)

Subject

Materials Chemistry,General Chemistry,Catalysis

Link

http://pubs.rsc.org/en/content/articlepdf/2020/NJ/D0NJ02592E

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