Hello! I have a question and I hope to discuss it with you
DDGANs abandon the assumption that the denoising distribution is Gaussian and use a conditional GAN to simulate this denoising distribution.
So, the acceleration model of DDPM (which actually only modified the sampling algorithm), such as DDIM, also has a data distribution and a non Markov chain for denoising. Can the conditional GANs in DDGANs fit the denoising distribution of DDIM, and will this further improve the generation speed