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Research · June 19, 2020

Denoising diffusion probabilistic models

A denoising diffusion model reached image quality that had belonged to adversarial networks.

Why it matters

Diffusion stopped being a described route to image synthesis and became a working one. The atlas holds the 2015 paper that described the process; this is the moment it produced numbers comparable to the best adversarial networks, and the generators that followed take this form.

The paper reports an Inception score of 9.46 and an FID of 3.17 on unconditional CIFAR-10, and sample quality on 256x256 LSUN comparable to ProgressiveGAN. The authors are Jonathan Ho, Ajay Jain and Pieter Abbeel of UC Berkeley. It is a result on those datasets, not a claim about every later image or video generator.

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June 19, 2020
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Sources gathered automatically · September 21, 2026
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evt-0485

The day the first version of the preprint appeared on arXiv.

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