backward stochastic differential equations

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Backward SDE Approach Targets Physics Consistency in Diffusion Models

A new arXiv preprint proposes using backward stochastic differential equations to enforce physics and measurement consistency when score-based diffusion models are applied to inverse problems. The authors argue that existing methods, such as heuristic guidance, periodic projections, or task-specific conditional training, are less principled. The work positions the approach as a general way to keep pretrained diffusion priors aligned with physical constraints.

diffusion/research/physics/generative-models