Methods › Computer Vision › Image Restoration Models › Conffusion
Confidence Intervals for Diffusion Models
Conffusion
Introduced by Eliahu Horwitz et al. in Conffusion: Confidence Intervals for Diffusion Models
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Given a corrupted input image, Con\textit{ffusion}, repurposes a pretrained diffusion model to generate lower and upper bounds around each reconstructed pixel. The true pixel value is guaranteed to fall within these bounds with probability p.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Conffusion: Confidence Intervals for Diffusion Models 17 Nov 2022 · 1 repository · arXiv:2211.09795
Tasks archive 2025-07-28
6 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Conformal Prediction | 1 |
| Facial Inpainting | 1 |
| Image Generation | 1 |
| Image Inpainting | 1 |
| Prediction Intervals | 1 |
| Super-Resolution | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections