Learning Diffusion Model from Noisy Measurement using Principled Expectation-Maximization Method

Diffusion models have demonstrated exceptional ability in modeling complex image distributions, making them versatile plug-and-play priors for solving imaging inverse problems. However, their reliance on large-scale clean datasets for training limits their applicability in scenarios where acquiring...

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Bibliographic Details

Published in:	Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) pp. 1 - 5
Main Authors:	Bai, Weimin, Tang, Weiheng, Ye, Enze, Chen, Siyi, Chen, Wenzheng, Sun, He
Format:	Conference Proceeding
Language:	English
Published:	IEEE 06.04.2025
Subjects:	Acoustic measurements Bayesian inference Computational imaging Convergence Diffusion models image priors Image reconstruction Imaging Inverse problems Noise measurement Signal processing algorithms Speech processing Training
ISSN:	2379-190X
Online Access:	Get full text
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