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Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial

Machine Learning 2025-07-08 v3 History and Overview

Abstract

This is an expository article on the score-based diffusion models, with a particular focus on the formulation via stochastic differential equations (SDE). After a gentle introduction, we discuss the two pillars in the diffusion modeling -- sampling and score matching, which encompass the SDE/ODE sampling, score matching efficiency, the consistency models, and reinforcement learning. Short proofs are given to illustrate the main idea of the stated results. The article is primarily a technical introduction to the field, and practitioners may also find some analysis useful in designing new models or algorithms.

Keywords

Cite

@article{arxiv.2402.07487,
  title  = {Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial},
  author = {Wenpin Tang and Hanyang Zhao},
  journal= {arXiv preprint arXiv:2402.07487},
  year   = {2025}
}