Physics-informed graph attention LSTM with a novel spatial season-aware GPD claims to outperform baselines and SEAS5 for extreme rainfall prediction across Thailand gauge stations.
GCNs were formulated for undirected graphs, operating on the normalised graph Laplacian
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Leveraging Teleconnections with Physics-Informed Graph Attention Networks for Long-Range Extreme Rainfall Forecasting in Thailand
Physics-informed graph attention LSTM with a novel spatial season-aware GPD claims to outperform baselines and SEAS5 for extreme rainfall prediction across Thailand gauge stations.