4 papers · 1 filter
TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting
Huanyu Zhang, Chang Xu, Yi-Fan Zhang +4
Time series forecasting plays a crucial role in data mining, driving rapid advancements across numerous industries. With the emergence of large models, time series foundation model…
InvDiff: Invariant Guidance for Bias Mitigation in Diffusion Models
Min Hou, Yueying Wu, Chang Xu +4
As one of the most successful generative models, diffusion models have demonstrated remarkable efficacy in synthesizing high-quality images. These models learn the underlying high-…
MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
Junjie Li, Yang Liu, Weiqing Liu +4
Generative models aim to simulate realistic effects of various actions across different contexts, from text generation to visual effects. Despite significant efforts to build real-…
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,…