23 citations · 28 across the 4 of their papers we have counts for
5 papers
Learning Regularization Functionals for Inverse Problems: A Comparative Study
Johannes Hertrich, Hok Shing Wong, Alexander Denker +16
In recent years, a variety of learned regularization frameworks for solving inverse problems in imaging have emerged. These offer flexible modeling together with mathematical insig…
Product of Gaussian Mixture Diffusion Models
Martin Zach, Erich Kobler, Antonin Chambolle +1
In this work we tackle the problem of estimating the density of a random variable by successive smoothing, such that the smoothed random variable fulfills the d…
Explicit Diffusion of Gaussian Mixture Model Based Image Priors
Martin Zach, Thomas Pock, Erich Kobler +1
In this work we tackle the problem of estimating the density of a random variable by successive smoothing, such that the smoothed random variable fulfills $(\partial_…
Stable Deep MRI Reconstruction using Generative Priors
Martin Zach, Florian Knoll, Thomas Pock
Data-driven approaches recently achieved remarkable success in magnetic resonance imaging (MRI) reconstruction, but integration into clinical routine remains challenging due to a l…
Computed Tomography Reconstruction using Generative Energy-Based Priors
Martin Zach, Erich Kobler, Thomas Pock
In the past decades, Computed Tomography (CT) has established itself as one of the most important imaging techniques in medicine. Today, the applicability of CT is only limited by…