For Gaussian mixture targets, diffusion discretization error and step complexity are controlled by latent entropy rather than ambient dimension.
Accelerating convergence of score-based diffusion models, provably
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The paper establishes an O(ε^{-4}) sample complexity bound for score estimation in diffusion models without requiring access to the empirical risk minimizer.
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When Diffusion Model Can Ignore Dimension: An Entropy-Based Theory
For Gaussian mixture targets, diffusion discretization error and step complexity are controlled by latent entropy rather than ambient dimension.
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Improved Sample Complexity For Diffusion Model Training Without Empirical Risk Minimizer Access
The paper establishes an O(ε^{-4}) sample complexity bound for score estimation in diffusion models without requiring access to the empirical risk minimizer.