Derives near-optimal nonasymptotic excess-risk bounds for Engression and reverse Markov Engression over Hölder classes via energy distance.
arXiv preprint arXiv:2012.08125 , year=
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Diffusion models with architecture improvements and classifier guidance achieve superior FID scores to GANs on unconditional and conditional ImageNet image synthesis.
Denoising Student distills the multi-step denoising process of score-based and diffusion models into a single forward pass, matching GAN sampling speed while producing comparable sample quality on CIFAR-10, CelebA, and 256x256 LSUN.
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Theoretical Analysis of Engression and Reverse Markov Engression
Derives near-optimal nonasymptotic excess-risk bounds for Engression and reverse Markov Engression over Hölder classes via energy distance.
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Diffusion Models Beat GANs on Image Synthesis
Diffusion models with architecture improvements and classifier guidance achieve superior FID scores to GANs on unconditional and conditional ImageNet image synthesis.
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Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed
Denoising Student distills the multi-step denoising process of score-based and diffusion models into a single forward pass, matching GAN sampling speed while producing comparable sample quality on CIFAR-10, CelebA, and 256x256 LSUN.