Urban Flow Prediction

Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning

[ORAL] KDD 2019, Research Track (acceptance rate: 14.2%)

Zheyi Pan*, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, Junbo Zhang

Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning

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.

Junbo Zhang, Yu Zheng, Dekang Qi

Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction