2026
Addressing Downward Memory Loss in Hierarchical GNN Forecasters Through Memory-Buffered Decoding
IJCAI 2026
Accurate spatio-temporal forecasting requires modeling interactions across multiple spatial and temporal scales. Existing Graph Neural Network (GNN) forecasters primarily operate at a single local scale, limiting their ability to capture global processes that govern system dynamics. Hierarchical GNN