MoleMCL: a multi-level contrastive learning framework for molecular pre-training
Xinyi Zhang,
Yanni Xu,
Changzhi Jiang
et al.
Abstract:Motivation
Molecular representation learning plays an indispensable role in crucial tasks such as property prediction and drug design. Despite the notable achievements of Molecular Pre-training Models (MPMs), current methods often fail to capture both the structural and feature semantics of molecular graphs. Moreover, while graph contrastive learning has unveiled new prospects, existing augmentation techniques often struggle to retain their core semantics. To overcome these limitations, we pr… Show more
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.