Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

To reduce the number of sampling steps in diffusion models, we propose to model the denoising distribution with conditional GANs. We show our model tackles the generative learning trilemma & achieves high sample quality, diversity & fast sampling.