#graph neural networks
Aug 2026
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.
· Lecture notes in computer sc... · 1 citation