ForcingDAS is a single diffusion-based model for data assimilation that unifies filtering and smoothing regimes via per-frame noise scheduling and reduces long-horizon error accumulation on non-Markovian observations.
These are the conversion factors between the data space (where the model and the observation operator act) and the raw physical space
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ForcingDAS: Unified and Robust Data Assimilation via Diffusion Forcing
ForcingDAS is a single diffusion-based model for data assimilation that unifies filtering and smoothing regimes via per-frame noise scheduling and reduces long-horizon error accumulation on non-Markovian observations.