On the Posterior Distribution in Denoising: Application to Uncertainty Quantification

24 September 2023

Papers citing "On the Posterior Distribution in Denoising: Application to Uncertainty Quantification"

15 / 15 papers shown

Title
Uncertainty Quantification for Machine Learning in Healthcare: A Survey L. J. L. Lopez Shaza Elsharief Dhiyaa Al Jorf Firas Darwish Congbo Ma Farah E. Shamout 26 0 0 04 May 2025
InvFussion: Bridging Supervised and Zero-shot Diffusion for Inverse Problems Noam Elata Hyungjin Chung Jong Chul Ye T. Michaeli Michael Elad DiffM 35 0 0 02 Apr 2025
A Simple Combination of Diffusion Models for Better Quality Trade-Offs in Image Denoising Jonas Dornbusch Emanuel Pfarr Florin-Alexandru Vasluianu Frank Werner Radu Timofte DiffM 55 0 0 18 Mar 2025
Conditional Distribution Quantization in Machine Learning Blaise Delattre Sylvain Delattre Alexandre Verine Alexandre Allauzen 45 0 0 11 Feb 2025
Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure Xiang Li Yixiang Dai Qing Qu DiffM AI4CE 23 5 0 31 Oct 2024
Shallow Diffuse: Robust and Invisible Watermarking through Low-Dimensional Subspaces in Diffusion Models Wenda Li Huijie Zhang Qing Qu WIGM 41 0 0 28 Oct 2024
Free Hunch: Denoiser Covariance Estimation for Diffusion Models Without Extra Costs Severi Rissanen Markus Heinonen Arno Solin DiffM 42 0 0 15 Oct 2024
PSC: Posterior Sampling-Based Compression Noam Elata T. Michaeli Michael Elad DiffM 36 0 0 13 Jul 2024
Hierarchical Uncertainty Exploration via Feedforward Posterior Trees E. Nehme Rotem Mulayoff T. Michaeli UQCV 29 2 0 24 May 2024
Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion Hila Manor T. Michaeli DiffM 17 25 0 15 Feb 2024
Uncertainty Visualization via Low-Dimensional Posterior Projections Omer Yair E. Nehme T. Michaeli UQCV 19 2 0 12 Dec 2023
Uncertainty Quantification via Neural Posterior Principal Components E. Nehme Omer Yair T. Michaeli UQCV 13 6 0 27 Sep 2023
Label-Efficient Semantic Segmentation with Diffusion Models Dmitry Baranchuk Ivan Rubachev A. Voynov Valentin Khrulkov Artem Babenko DiffM VLM 187 508 0 06 Dec 2021
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 262 10,183 0 12 Dec 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015