Diffusion Models
Diffusion Models Many recent papers and blogs [1-4] have provided a good overview of diffusion models. In this note, I will summarize some high-level understandings towards the diffusion models and write down some key steps in the derivations. Summary DDPM is parameterized as a Markov chain which means that the latent variables depend only on the previous (or following) timestep. However, DDIM shows that it is indeed not necessary. The forward prcess of DDPM is a chain of additive Gaussian noise channels and the variance of the noises are pre-defined, i....