3 papers
cs.LG2026
Towards a Unified Generative Model for Scarce Time Series with Domain Experts
Zihao Yao, Qi Zheng, Jiankai Zuo +1
Synthesizing realistic time series with generative models has wide-ranging applications in real-world scenarios. Despite recent progress, most existing methods are trained under th…
cs.LG2025
DiM-TS: Bridge the Gap between Selective State Space Models and Time Series for Generative Modeling
Zihao Yao, Jiankai Zuo, Yaying Zhang
Time series data plays a pivotal role in a wide variety of fields but faces challenges related to privacy concerns. Recently, synthesizing data via diffusion models is viewed as a…
cs.LG2024
ST-ReP: Learning Predictive Representations Efficiently for Spatial-Temporal Forecasting
Qi Zheng, Zihao Yao, Yaying Zhang
Spatial-temporal forecasting is crucial and widely applicable in various domains such as traffic, energy, and climate. Benefiting from the abundance of unlabeled spatial-temporal d…