Urban Flow Prediction
Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning
[ORAL] KDD 2019, Research Track (acceptance rate: 14.2%)
Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction
We proposed a deep-learning-based approach, called ST-ResNet, to collectively forecast the inflow and outflow of crowds in each and every region of a city.