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Sheng-Wei Ji

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Open access Sep 2026

MG2CL: Multi-Granularity Graph Contrastive Learning for Skeleton-Based Action Recognition

Skeleton-based action recognition has gained increasing attention as a robust alternative to RGB-based methods due to its resilience to background clutter and lighting variations. Existing approaches have achieved notable progress, particularly with graph-based models that capture topological and temporal patterns of h...

Pensong Wang, Zhi-Ze Wu, Xin Chen et al. · 0 citations
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. · 0 citations
Book Open access Aug 2026

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

Molecular properties are often governed by a small number of local substructures, or motifs, whose topologies can vary drastically across molecules. Existing molecular representation learning approaches typically embed all motifs into a single Euclidean or fixed-curvature space, which fails to capture the motif-level t...

Fei Liu, Wen-Kai Lu, Feilong Wang et al. · 0 citations

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