A Global-Local Graph Attention Network for Traffic Forecasting

In three linesNew arXiv paper proposing GLGAT (Global-Local Graph Attention Network) for traffic forecasting. The model combines a global attention matrix for the entire graph with local attention matrices per vertex, using pairwise encoding and event-based adjacency matrix. Experiments on two real-world traffic datasets show competitive performance against state-of-the-art baselines.

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