Understanding Non-Asymptotic Convergence in Diffusion-Based Generative Models

The author explores non-asymptotic convergence in diffusion-based generative models, focusing on deterministic and stochastic samplers, providing insights into the impact of score estimation errors and proposing accelerated variants.