A spatiotemporal graph network with a generalized Pareto loss is introduced and shown to outperform most benchmarks for Delhi PM2.5, PM10, and NO2 forecasting.
, author Segerdahl, C.O
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E-STGCN: Extreme Spatiotemporal Graph Convolutional Networks for Air Quality Forecasting
A spatiotemporal graph network with a generalized Pareto loss is introduced and shown to outperform most benchmarks for Delhi PM2.5, PM10, and NO2 forecasting.