Multi-scale cross-attention transformer via graph embeddings for few-shot molecular property prediction

Luis H.M. Torres; Bernardete Ribeiro; Joel P. Arrais

doi:10.1016/j.asoc.2024.111268

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Multi-scale cross-attention transformer via graph embeddings for few-shot molecular property prediction

Luis H.M. Torres Bernardete Ribeiro Joel P. Arrais

Year: 2024 Journal: Applied Soft Computing Vol: 153 Pages: 111268-111268 Publisher: Elsevier BV

DOI: 10.1016/j.asoc.2024.111268

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Keywords:

Computer science Embedding Molecular graph Graph Property (philosophy) Transformer Theoretical computer science Machine learning Artificial intelligence Data mining Feature learning

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Computational Drug Discovery Methods

Physical Sciences → Computer Science → Computational Theory and Mathematics

Machine Learning in Materials Science

Physical Sciences → Materials Science → Materials Chemistry

Protein Structure and Dynamics

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Multi-scale cross-attention transformer via graph embeddings for few-shot molecular property prediction

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