Various types of diffusion model sampling. The training phase consists of two processes (forward and reverse). The reverse process resembles a denoising procedure in which a score function network |$\mathbf {s}_{\boldsymbol{\theta }^{*}}$| is employed to learn the mapping from noisy to an image of the noise. After the training, a (reverse) intermediate sampling is used to perform regularization for EFWI.