WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution

20 January 2022

Papers citing "WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution"

5 / 5 papers shown

Title
Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction Moritz Piening Fabian Altekrüger J. Hertrich Paul Hagemann Andrea Walther Gabriele Steidl 19 5 0 27 Dec 2023
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems Fabian Altekrüger Paul Hagemann Gabriele Steidl TPM 16 9 0 28 Mar 2023
Generalized Normalizing Flows via Markov Chains Paul Hagemann J. Hertrich Gabriele Steidl BDL DiffM AI4CE 17 22 0 24 Nov 2021
Posterior Sampling for Image Restoration using Explicit Patch Priors Roy Friedman Yair Weiss 33 5 0 20 Apr 2021
Invertible Neural Networks versus MCMC for Posterior Reconstruction in Grazing Incidence X-Ray Fluorescence A. Andrle N. Farchmin Paul Hagemann Sebastian Heidenreich V. Soltwisch Gabriele Steidl 58 16 0 05 Feb 2021