A Memory-Efficient SubGraph Learning Method for Urban Spatio-Temporal Forecasting
Spatio-temporal graph learning has been widely applied to urban spatio-temporal forecasting tasks, analyzing the relationships between data to achieve accurate predictions. However, in recent years, model structures have become increasingly complex in pursuit of higher performance, resulting in greater computational co...