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Conference Open access Sep 2026

H²SCAN: Adaptive Time Series Representation Learning via Heterogeneous Hypergraph Structure-aware Contrasts

H²SCAN is proposed, a novel augmentation-free framework that derives contrastive supervision directly from graph topology and outperforms existing methods by modeling high-order multi-domain dependencies and preserving the semantic integrity of time series data.

Biao Chen, Zi-Jie Tang, Junhua Fang et al. · 0 citations

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