spatial-modeling

论文提出 FireGraphNet，将12小时野火蔓延预测建模为有向 H3 图上的节点分类任务，在加州测试火灾上平均精度达到最强距离基线的1.7–1.9倍，并分析了图消息传递对预测能力的贡献。

M2Weather introduces a benchmark for joint multi-station and multi-variable weather forecasting, collecting 2,809 stations across France, Europe, and Global scales, and proposing a plug-and-play adapter that improves forecasting by modeling station-variable relationships.

This paper introduces GeoID-PINN, a physics-informed neural network for regional epidemic inference that incorporates geographic coupling via a spatial source-composition matrix. It demonstrates that accurate trajectory forecasts do not guarantee correct recovery of regional dependence structures, using simulations and COVID-19 data from Louisiana counties.