Diffusion Model from Scratch
Abstract
Diffusion generative models are currently the most popular generative models. However, their underlying modeling process is quite complex, and starting directly with the seminal paper Denoising Diffusion Probability Model (DDPM) can be challenging. This paper aims to assist readers in building a foundational understanding of generative models by tracing the evolution from VAEs to DDPM through detailed mathematical derivations and a problem-oriented analytical approach. It also explores the core ideas and improvement strategies of current mainstream methodologies, providing guidance for undergraduate and graduate students interested in learning about diffusion models.
Keywords
Cite
@article{arxiv.2412.10824,
title = {Diffusion Model from Scratch},
author = {Wang Zhen and Dong Yunyun},
journal= {arXiv preprint arXiv:2412.10824},
year = {2024}
}
Comments
There were problems with the typography of our illustrations, and there were problems with the derivation of the 200-step formula