From Score Learning to Discretized Sampling: An End-to-End Generalization Analysis of Diffusion Models
This work establishes a unified convergence and generalization framework for score-based diffusion models parameterized by practical ResNet-type architectures and quantitatively characterize how the training sample size, temporal discretization grids, and optimization accuracy jointly control the final fidelity of samp...