Learning effective molecular feature representation to facilitate molecular property prediction is of great significance for drug discovery. Recently, there has been a surge of interest in ...

Molecular graph representation learning has shown considerable strength in molecular analysis and drug discovery. Due to the difficulty of obtaining molecular property labels, pre-training models ...

Self-supervised learning allows a neural network to figure out for itself what matters. The process might be what makes our own brains so successful. For a decade now, many of the most impressive ...