AI RESEARCH
(HB-ARFM) History-Bootstrapped Flow Matching for Inverse Boiling Reconstruction
arXiv CS.AI
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ArXi:2606.00349v1 Announce Type: cross Reconstructing spatiotemporal fields from partial observations is fundamental to scientific inference, from inferring atmospheric states from satellite data to recovering fluid states from imaging. When observations are incomplete, the inverse problem is fundamentally ill-posed: even when the underlying PDE dynamics are Markovian in the full state, partial observation operators induce a non-Markovian posterior that cannot be resolved from a single timestep.