Geometric deep learning for molecular property predictions with chemical accuracy across chemical space

Abstract Chemical engineers heavily rely on precise knowledge of physicochemical properties to model chemical processes. Despite the growing popularity of deep learning, it is only rarely applied for property prediction due to data scarcity and limited accuracy for compounds in industrially-relevant...

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Bibliographic Details

Published in:	Journal of Cheminformatics
Main Authors:	Maarten R. Dobbelaere, István Lengyel, Christian V. Stevens, Kevin M. Van Geem
Format:	Article
Language:	English
Published:	BMC 2024-08-01
Subjects:	Artificial intelligence Deep learning Thermochemistry Liquid-phase thermodynamics Representation learning
Online Access:	https://doi.org/10.1186/s13321-024-00895-0