A forward diffusion process adds noise iteratively to data until it is unstructured, and a neural network learns the reverse process to generate new samples from the original distribution.
Occlusion models for natural images: A statistical study of a scale-invariant dead leaves model
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Deep Unsupervised Learning using Nonequilibrium Thermodynamics
A forward diffusion process adds noise iteratively to data until it is unstructured, and a neural network learns the reverse process to generate new samples from the original distribution.