What are the limitations of diffusion?
Diffusion models offer superior stability during training, high-quality output, better controllability, and more consistent results compared to GANs. They can generate diverse and realistic content with fewer artifacts. Their principled mathematical foundation makes them more reliable and easier to optimize for specific tasks. The main goal of diffusion models is to learn a high-quality data…