Flow Matching with Missing Data
Missing-Data Flow Matching (MDFM) trains flow matching models directly from data with missing coordinates by treating those missing values as latent variables. It proves this correction is exact, meaning training on incomplete data is mathematically equivalent to training on complete data under certain conditions. This method handles real-world missingness better than standard techniques.