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Author

Zonghan Wu

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When GNNs Fail: Quantifying and Overcoming Temporal Correlation Volatility in Time Series

This work proposes Graph Layer for Inference in Dynamic En- vironments (GLIDE), a novel GNN layer enhanced by two theoretically grounded design mechanisms that significantly improve learning under dynamic topology while preserving robustness in static scenarios.

Chen Shao, Yue Wang, Zhen-Yi Zhu et al. · 1 citation

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