Definition

Diffusion Model

A diffusion model learns to reverse noise. Training adds noise to real images step by step until nothing remains, then teaches a network to undo one step at a time. Generation starts from pure static and denoises repeatedly, sculpting structure out of chaos over tens to hundreds of steps. Compared with GANs it trains stably, produces more diverse output, and can be guided by text at every step.