Progressive Graph Convolutional Networks for Spatial-Temporal Traffic Forecasting

The complex spatial-temporal correlations in traffic data make the traffic forecasting problem challenging. The proposed model captures the time-varying spatial correlations by progressively adapting to data used for forecasting tasks.