5 citations · 6 across the 9 of their papers we have counts for
4 papers · 1 filter
Spatial-Temporal Feedback Diffusion Guidance for Controlled Traffic Imputation
Xiaowei Mao, Huihu Ding, Yan Lin +6
Imputing missing values in spatial-temporal traffic data is essential for intelligent transportation systems. Among advanced imputation methods, score-based diffusion models have d…
RIPCN: A Road Impedance Principal Component Network for Probabilistic Traffic Flow Forecasting
Haochen Lv, Yan Lin, Shengnan Guo +5
Accurate traffic flow forecasting is crucial for intelligent transportation services such as navigation and ride-hailing. In such applications, uncertainty estimation in forecastin…
STD-PLM: Understanding Both Spatial and Temporal Properties of Spatial-Temporal Data with PLM
YiHeng Huang, Xiaowei Mao, Shengnan Guo +5
Spatial-temporal forecasting and imputation are important for real-world intelligent systems. Most existing methods are tailored for individual forecasting or imputation tasks but…
DRL4Route: A Deep Reinforcement Learning Framework for Pick-up and Delivery Route Prediction
Xiaowei Mao, Haomin Wen, Hengrui Zhang +5
Pick-up and Delivery Route Prediction (PDRP), which aims to estimate the future service route of a worker given his current task pool, has received rising attention in recent years…