Spiers Memorial Lecture: How to do impactful research in artificial intelligence for chemistry and materials science.
Journal
Faraday discussions
ISSN: 1364-5498
Titre abrégé: Faraday Discuss
Pays: England
ID NLM: 9212301
Informations de publication
Date de publication:
14 Oct 2024
14 Oct 2024
Historique:
medline:
14
10
2024
pubmed:
14
10
2024
entrez:
14
10
2024
Statut:
aheadofprint
Résumé
Machine learning has been pervasively touching many fields of science. Chemistry and materials science are no exception. While machine learning has been making a great impact, it is still not reaching its full potential or maturity. In this perspective, we first outline current applications across a diversity of problems in chemistry. Then, we discuss how machine learning researchers view and approach problems in the field. Finally, we provide our considerations for maximizing impact when researching machine learning for chemistry.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM