diffusion models

{
  "id": "MLC-T-CYB-001368",
  "term": "diffusion models",
  "field": "Cybersecurity",
  "definition": "A class of latent variable generative models consisting of three major components: a forward process, a reverse process, and a sampling procedure. The goal of the diffusion model is to learn a diffusion process that generates the probability distribution of a given dataset. It is widely used in computer vision on a variety of tasks, including image denoising, inpainting, super-resolution, and image generation.",
  "references": [
    "NIST AI 100-2e2025",
    "NIST CSRC Glossary"
  ],
  "url": "https://mlchart.com/terminology/cybersecurity/diffusion-models/"
}