4 ms·
Or the two can be combined : https://nvlabs.github.io/denoising-diffusion-gan/index.html https://nvlabs.github.io/denoising-diffusion-gan/index.html
by mdda 4y ago
Or the two can be combined : https://nvlabs.github.io/denoising-diffusion-gan/index.html https://nvlabs.github.io/denoising-diffusion-gan/index.html
- oofbey 4y agoSounds like it gets the worst of both worlds? The difficult training of a GAN with the slow runtime of a diffusion model.
- mdda 4y agoCould be... Except their page (should you choose to believe it, of course) specifically addresses the advantages: """ "Advantages over Traditional GANs" : Thus, we observe that our model exhibits _better training stability_ and mode coverage. "Why is Sampling from Denoising Diffusion Models so Slow?" : After training, we generate novel instances by sampling from noise and iteratively denoising it _in a few steps_ using our denoising diffusion GAN generator. """