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cs.CV2026
Product-of-Gaussian-Mixture Diffusion Models for Joint Nonlinear MRI Reconstruction
Laurenz Nagler, Martin Zach, Thomas Pock
Recently, diffusion models have attracted considerable attention for magnetic resonance image reconstruction due to their high sample quality. However, most existing methods rely o…
cs.CV2024
Posterior-Variance-Based Error Quantification for Inverse Problems in Imaging
Dominik Narnhofer, Andreas Habring, Martin Holler +1
In this work, a method for obtaining pixel-wise error bounds in Bayesian regularization of inverse imaging problems is introduced. The proposed method employs estimates of the post…