3 papers
cs.LG2025
PhaseFormer: From Patches to Phases for Efficient and Effective Time Series Forecasting
Yiming Niu, Jinliang Deng, Yongxin Tong
Periodicity is a fundamental characteristic of time series data and has long played a central role in forecasting. Recent deep learning methods strengthen the exploitation of perio…
cs.LG2025
Accurate and Efficient Multivariate Time Series Forecasting via Offline Clustering
Yiming Niu, Jinliang Deng, Lulu Zhang +2
Accurate and efficient multivariate time series (MTS) forecasting is essential for applications such as traffic management and weather prediction, which depend on capturing long-ra…
cs.LG2025
Understanding and Mitigating the High Computational Cost in Path Data Diffusion
Dingyuan Shi, Lulu Zhang, Yongxin Tong +1
Advancements in mobility services, navigation systems, and smart transportation technologies have made it possible to collect large amounts of path data. Modeling the distribution…