ForcingDAS: Unified and Robust Data Assimilation via Diffusion Forcing
Researchers have developed ForcingDAS, a new framework for data assimilation that unifies filtering and smoothing approaches. This method uses Diffusion Forcing to learn a joint-trajectory prior, which helps in capturing long-horizon temporal dependencies and reducing error accumulation, unlike traditional frame-to-frame transition models. ForcingDAS has demonstrated competitive or superior performance compared to specialized baselines across various applications, including weather forecasting and atmospheric state estimation, by using a single trained model for the entire spectrum of inference tasks. AI