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VaryST: Generalizable Spatio-Temporal Forecasting Beyond the Closed-World Setting
Shengnan Guo, Jinjun Cheng, Xiaowei Mao +7
Spatio-temporal forecasting is fundamental to many real-world systems, yet deployment environments are inherently varying: temporal distributions may evolve, spatial domains may ch…
A Survey and Benchmarking of Spatial-Temporal Traffic Data Imputation Models
Shengnan Guo, Tonglong Wei, Yiheng Huang +6
Traffic data imputation is a critical preprocessing step in intelligent transportation systems, underpinning the reliability of downstream transportation services. Despite substant…
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…
Diff-RNTraj: A Structure-aware Diffusion Model for Road Network-constrained Trajectory Generation
Tonglong Wei, Youfang Lin, Shengnan Guo +5
Trajectory data is essential for various applications as it records the movement of vehicles. However, publicly available trajectory datasets remain limited in scale due to privacy…