Derives an explicit risk bound for a diffusion-based drift estimator in SDEs by decomposing error into Euler-Maruyama discretization, score approximation, noise initialization, and sampling variance.
Drift estimation for stochastic differential equations with denoising diffusion models
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Error Bounds for a Diffusion Model-Based Drift Estimator
Derives an explicit risk bound for a diffusion-based drift estimator in SDEs by decomposing error into Euler-Maruyama discretization, score approximation, noise initialization, and sampling variance.