Machine learning models for catalytic asymmetric reactions of simple alkenes: from enantioselectivity predictions to chemical insights
Abstract
Enantioselectivity predictions of catalytic asymmetric transformations of alkenes using a class imbalance-aware AttentiveFP machine learning model offer good accuracy and chemically meaningful interpretability.
Fields of Study & Subjects
Machine Learning in Materials Science
Catalysis and Oxidation Reactions
Asymmetric Hydrogenation and Catalysis
Publication details
- Journal / source
- Digital Discovery
- Publisher
- Royal Society of Chemistry (RSC)
- Volume
- 5
- Issue
- 4
- Pages
- 1718–1735
- Publication date
- 1 January 2026
- Language
- EN