Denoising

A core process in diffusion models where a model learns to progressively remove noise from a corrupted input to recover a clean output. During training, noise is added to data in steps; during generation, the model reverses this process, starting from pure noise and gradually refining it into a coherent image, audio clip, or other output.
See also: diffusion model, diffusion, generative AI.