The Math Behind Diffusion Models: From Score Matching to Stable Diffusion 3

Forward and Reverse Markov Chains

Diffusion models conceptualize image generation as gradually reversing a thermodynamic noise injection process. By training neural networks to predict noise vectors at arbitrary timesteps, the system reconstructs sharp imagery from pure Gaussian static.