Accurate prediction of molecular properties is crucial for drug discovery, yet existing models often struggle with multi-level feature interaction. Here, the authors introduce the hierarchical interaction message net (HimNet), which enhances representation learning across atomic, motif, and molecular levels, achieving superior performance in property prediction tasks.
- Huiyang Hong
- Xinkai Wu
- Yuquan Li