Learning to Efficiently Sample from Diffusion Probabilistic Models

Daniel Watson, Jonathan Ho, Mohammad Norouzi +1

Denoising Diffusion Probabilistic Models (DDPMs) have emerged as a powerful family of generative models that can yield high-fidelity samples and competitive log-likelihoods across…