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Non-asymptotic Convergence of Stochastic Gradient Descent in Score-based Generative Models
Score-based Generative Models (SGMs) have achieved impressive performance in data generation across a wide range of applications. While the statistical properties of their sampling procedures are increasingly well understood, the optimization dynamics underlying their training remain less explored.
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