Tag: diffusion

Diffusion probabilistic models were originally proposed as a latent variable generative model inspired by non-equilibrium thermodynamics. The essential idea of diffusion models is to systematically perturb the structure in a data distribution through a forward diffusion process, and then recover the structure by learning a reverse diffusion process, resulting in a highly flexible and tractable generative model.