MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process

arXiv:2403.05751v1 Announce Type: new
Abstract: Recently, diffusion probabilistic models have attracted attention in generative time series forecasting due to their remarkable capacity to generate high-fidelity samples. However, the effective utilization of their strong modeling ability in the probabilistic time series forecasting task remains an open question, partially due to the challenge of instability arising from their stochastic nature. To address this challenge, we introduce a novel Multi-Granularity Time Series Diffusion (MG-TSD) model, which achieves state-of-the-art predictive performance by leveraging the …

abstract arxiv attention capacity cs.ai cs.lg diffusion diffusion models fidelity forecasting generate generative however modeling process question samples series time series time series forecasting type