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cs.LG2025
TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts
Yu-Hao Huang, Chang Xu, Yueying Wu +2
Time series generation models are crucial for applications like data augmentation and privacy preservation. Most existing time series generation models are typically designed to ge…
cs.LG2024
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang Xu +3
Recently, diffusion probabilistic models have attracted attention in generative time series forecasting due to their remarkable capacity to generate high-fidelity samples. However,…