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Research questionHow can molecular property predictors retain substructure and graph-distance information in compact representations without external pretraining?Compression can discard the substructures and spatial relationships that influence molecular properties. The challenge is to preserve these relationships while keeping representations and prediction models efficient to train and use.
AI
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Machine Learning
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Statistical Machine Learning
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Latest papersRecent research connected to this question, newest first.WEECFP-SuRGE: Wide Embedded Extended Connectivity Fingerprint with Substructure Rotary Graph-distance EncodingThe source evaluates a continuous molecular fingerprint and a transformer encoding shortest-path information through attention, without external pretraining. Evidence covers ADMET and regression tasks as well as reconstruction and graph-distance analyses on the reported datasets, so applicability beyond those settings remains unestablished.research paper · Sep 4, 2026
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