StaTS: Spectral Trajectory Schedule Learning for Adaptive Time Series Forecasting with Frequency Guided Denoiser

Researchers introduce StaTS, a new diffusion model for time series forecasting that learns adaptive noise schedules and uses frequency-guided denoising. The model addresses limitations of fixed noise schedules in existing diffusion models by incorporating spectral regularization and data-adaptive scheduling for improved structural preservation.