TimeDiT: Diffusion Transformers Foundation Model for Time Series Forecasting

This work introduces TimeDiT, a diffusion transformer model that combines transformer-based temporal dependency learning with diffusion-based probabilistic sampling and employs a unified masking mechanism to harmonize training and inference across diverse tasks.