GLSTaGAT is a spatial-temporal graph attention network using data-driven fusion graphs, global-local blocks, node normalization, and a transformer encoder to outperform baselines on real-world network traffic datasets.
Koster, Manuel Kutschka, and Christian Raack
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Global-local Spatial-temporal Aware Graph Attention Network for Network Traffic Forecasting
GLSTaGAT is a spatial-temporal graph attention network using data-driven fusion graphs, global-local blocks, node normalization, and a transformer encoder to outperform baselines on real-world network traffic datasets.