AI RESEARCH
Cross-Domain Molecular Relational Learning: Leveraging Chemical Structure-Activity Analysis
arXiv CS.LG
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ArXi:2605.16799v1 Announce Type: new Recent advances in molecular representation integrates molecular topological and visual modalities, opening new avenues for precise Molecular Relational Learning (MRL). Existing MRL methods focus on intra-domain modeling, and their inherent domain-closed effect limits applicability to molecular science, particularly in elucidating cross-domain interaction mechanisms. Consequently, the imperative for Cross-Domain Molecular Relational Learning has become increasingly pressing. Benefiting from structure-activity analysis, we propose the Domain Adversarial.