11 citations · 17 across the 33 of their papers we have counts for
8 papers · 1 filter
Air Quality Prediction with Physics-Guided Dual Neural ODEs in Open Systems
Jindong Tian, Yuxuan Liang, Ronghui Xu +6
Air pollution significantly threatens human health and ecosystems, necessitating effective air quality prediction to inform public policy. Traditional approaches are generally cate…
SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation
Hongfan Gao, Wangmeng Shen, Xiangfei Qiu +3
Probabilistic time series imputation has been widely applied in real-world scenarios due to its ability for uncertainty estimation and denoising diffusion probabilistic models~(DDP…
CATCH: Channel-Aware multivariate Time Series Anomaly Detection via Frequency Patching
Xingjian Wu, Xiangfei Qiu, Zhengyu Li +5
Anomaly detection in multivariate time series is challenging as heterogeneous subsequence anomalies may occur. Reconstruction-based methods, which focus on learning normal patterns…
TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting
Zhe Li, Xiangfei Qiu, Peng Chen +8
Time Series Forecasting (TSF) is key functionality in numerous fields, such as financial investment, weather services, and energy management. Although increasingly capable TSF meth…
Orca: Ocean Significant Wave Height Estimation with Spatio-temporally Aware Large Language Models
Zhe Li, Ronghui Xu, Jilin Hu +4
Significant wave height (SWH) is a vital metric in marine science, and accurate SWH estimation is crucial for various applications, e.g., marine energy development, fishery, early…
Efficient Stochastic Routing in Path-Centric Uncertain Road Networks -- Extended Version
Chenjuan Guo, Ronghui Xu, Bin Yang +4
The availability of massive vehicle trajectory data enables the modeling of road-network constrained movement as travel-cost distributions rather than just single-valued costs, the…
TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
Xiangfei Qiu, Jilin Hu, Lekui Zhou +8
Time series are generated in diverse domains such as economic, traffic, health, and energy, where forecasting of future values has numerous important applications. Not surprisingly…
UVTM: Universal Vehicle Trajectory Modeling with ST Feature Domain Generation
Yan Lin, Jilin Hu, Shengnan Guo +4
Vehicle movement is frequently captured in the form of GPS trajectories, i.e., sequences of timestamped GPS locations. Such data is widely used for various tasks such as travel-tim…