Unified and explainable molecular representation learning for imperfectly annotated data from the hypergraph view
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DOI: 10.1038/s41467-025-63730-6
Abstract: Molecular representation learning (MRL) has shown promise in accelerating drug development by predicting chemical properties. However, imperfectly annotation among datasets pose challenges in model design and explainability. In this work, we formulate molecules and corresponding… read more here.
Keywords: explainable molecular; representation learning; learning imperfectly; molecular representation ... See more keywords