Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances

Score-based generative modeling with probability flow ordinary differential equations (ODEs) has achieved remarkable success in a variety of applications. While various fast ODE-based samplers have been proposed in the literature and employed in practice, the theoretical understandings about convergence properties of the probability flow ODE are still quite limited. In this paper, we provide the first non-asymptotic convergence analysis for a general class of probability flow ODE samplers in 2-Wasserstein distance, assuming accurate score estimates. We then consider various examples …

analysis applications convergence cs.lg differential diffusion diffusion models flow general generative generative modeling literature math.pr modeling ordinary practice probability stat.ml success