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Fei-Long Wang

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Book Open access Aug 2026

Capturing Motif Topological Diversity via Geometry-Adaptive Riemannian Molecular Representation Learning

A geometry-adaptive Riemannian framework for molecular representation learning, which explicitly models motifs as the basic units and learns their embeddings across multiple constant-curvature spaces, offering a general and scalable framework for scientific molecular modeling.

Fei Liu, Wen-Kai Lu, Fei-Long Wang et al. · Proceedings of the 32nd ACM... · 0 citations