The motivation for this study came from the task of analysing the kineti...
Manifold-valued signal- and image processing has received attention due ...
We demonstrate the relevance of an algorithm called generalized iterativ...
Sliced optimal transport reduces optimal transport on multi-dimensional
...
Conditional generative models became a very powerful tool to sample from...
Score-based diffusion models (SBDM) have recently emerged as state-of-th...
Wasserstein gradient flows of maximum mean discrepancy (MMD) functionals...
This paper provides results on Wasserstein gradient flows between measur...
The aim of this paper is twofold. Based on the geometric Wasserstein tan...
The method of common lines is a well-established reconstruction techniqu...
Learning neural networks using only a small amount of data is an importa...
Gromov-Wasserstein (GW) distances are generalizations of Gromov-Haussdor...
Gromov-Wasserstein distances are generalization of Wasserstein distances...
Normalizing flows, diffusion normalizing flows and variational autoencod...
To overcome topological constraints and improve the expressiveness of
no...
Based on the analysis of variance (ANOVA) decomposition of functions whi...
In this paper, we study the mathematical imaging problem of optical
diff...
Grazing incidence X-ray fluorescence is a non-destructive technique for
...
In this work we consider the problem of identification and reconstructio...
In this paper, we introduce convolutional proximal neural networks (cPNN...
Despite the rapid development of computational hardware, the treatment o...
The topic of this study lies in the intersection of two fields. One is
r...
Principal component analysis (PCA) is known to be sensitive to outliers,...
Inertial algorithms for minimizing nonsmooth and nonconvex functions as ...
The stochastic inverse eigenvalue problem aims to reconstruct a stochast...
The aim of this paper is twofold. First, we show that a certain concaten...
In this paper, we consider maximum likelihood estimation of the degree o...
The contribution of this paper is twofold: First, we prove existence and...
The piecewise constant Mumford-Shah (PCMS) model and the Rudin-Osher-Fat...
Colorization of gray-scale images relies on prior color information.
Exa...
Nonlocal patch-based methods, in particular the Bayes' approach of Lebru...
Variational methods in imaging are nowadays developing towards a quite
u...