Broadening Target Distributions for Accelerated Diffusion Models via a Novel Analysis Approach

Understand

Accelerated diffusion models hold the potential to significantly enhance the efficiency of standard diffusion processes.

• Theoretically, these models have been shown to achieve faster convergence rates than the standard $\mathcal O(1/\epsilon^2)$ rate of vanilla diffusion models, where $\epsilon$ denotes the target accuracy.
• However, current theoretical studies have established the acceleration advantage only for restrictive target distribution classes, such as those with smoothness conditions imposed along the entire sampling path or with bounded support.
• In this work, we significantly broaden the target distribution classes with a new accelerated stochastic DDPM sampler.