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08/22/2023
A Study of Particle Motion in the Presence of Clusters
The motivation for this study came from the task of analysing the kineti...
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07/20/2023
Denoising of Sphere- and SO(3)-Valued Data by Relaxed Tikhonov Regularization
Manifold-valued signal- and image processing has received attention due ...
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05/11/2023
Generalized Iterative Scaling for Regularized Optimal Transport with Affine Constraints: Application Examples
We demonstrate the relevance of an algorithm called generalized iterativ...
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04/18/2023
Sliced Optimal Transport on the Sphere
Sliced optimal transport reduces optimal transport on multi-dimensional ...
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03/28/2023
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems
Conditional generative models became a very powerful tool to sample from...
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03/08/2023
Multilevel Diffusion: Infinite Dimensional Score-Based Diffusion Models for Image Generation
Score-based diffusion models (SBDM) have recently emerged as state-of-th...
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01/27/2023
Neural Wasserstein Gradient Flows for Maximum Mean Discrepancies with Riesz Kernels
Wasserstein gradient flows of maximum mean discrepancy (MMD) functionals...
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01/11/2023
Wasserstein Gradient Flows of the Discrepancy with Distance Kernel on the Line
This paper provides results on Wasserstein gradient flows between measur...
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11/02/2022
Wasserstein Steepest Descent Flows of Discrepancies with Riesz Kernels
The aim of this paper is twofold. Based on the geometric Wasserstein tan...
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09/16/2022
Motion Detection in Diffraction Tomography by Common Circle Methods
The method of common lines is a well-established reconstruction techniqu...
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05/24/2022
PatchNR: Learning from Small Data by Patch Normalizing Flow Regularization
Learning neural networks using only a small amount of data is an importa...
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05/13/2022
Multi-Marginal Gromov-Wasserstein Transport and Barycenters
Gromov-Wasserstein (GW) distances are generalizations of Gromov-Haussdor...
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12/22/2021
On a linear Gromov-Wasserstein distance
Gromov-Wasserstein distances are generalization of Wasserstein distances...
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11/24/2021
A Unified Approach to Variational Autoencoders and Stochastic Normalizing Flows via Markov Chains
Normalizing flows, diffusion normalizing flows and variational autoencod...
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09/23/2021
Stochastic Normalizing Flows for Inverse Problems: a Markov Chains Viewpoint
To overcome topological constraints and improve the expressiveness of no...
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05/31/2021
Sparse ANOVA Inspired Mixture Models
Based on the analysis of variance (ANOVA) decomposition of functions whi...
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04/16/2021
Fourier reconstruction for diffraction tomography of an object rotated into arbitrary orientations
In this paper, we study the mathematical imaging problem of optical diff...
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02/05/2021
Invertible Neural Networks versus MCMC for Posterior Reconstruction in Grazing Incidence X-Ray Fluorescence
Grazing incidence X-ray fluorescence is a non-destructive technique for ...
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01/27/2021
Super-Resolution for Doubly-Dispersive Channel Estimation
In this work we consider the problem of identification and reconstructio...
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11/04/2020
Convolutional Proximal Neural Networks and Plug-and-Play Algorithms
In this paper, we introduce convolutional proximal neural networks (cPNN...
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09/16/2020
PCA Reduced Gaussian Mixture Models with Applications in Superresolution
Despite the rapid development of computational hardware, the treatment o...
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06/29/2020
Transfer Operators from Optimal Transport Plans for Coherent Set Detection
The topic of this study lies in the intersection of two fields. One is r...
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05/11/2020
Robust PCA via Regularized REAPER with a Matrix-Free Proximal Algorithm
Principal component analysis (PCA) is known to be sensitive to outliers,...
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05/05/2020
Inertial Stochastic PALM and its Application for Learning Student-t Mixture Models
Inertial algorithms for minimizing nonsmooth and nonconvex functions as ...
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04/15/2020
A New Constrained Optimization Model for Solving the Nonsymmetric Stochastic Inverse Eigenvalue Problem
The stochastic inverse eigenvalue problem aims to reconstruct a stochast...
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12/19/2019
Parseval Proximal Neural Networks
The aim of this paper is twofold. First, we show that a certain concaten...
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10/15/2019
Alternatives of the EM Algorithm for Estimating the Parameters of the Student-t Distribution
In this paper, we consider maximum likelihood estimation of the degree o...
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10/12/2018
Multivariate Myriad Filters based on Parameter Estimation of Student-t Distributions
The contribution of this paper is twofold: First, we prove existence and...
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07/26/2018
Linkage between Piecewise Constant Mumford-Shah model and ROF model and its virtue in image segmentation
The piecewise constant Mumford-Shah (PCMS) model and the Rudin-Osher-Fat...
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06/01/2017
Examplar-Based Face Colorization Using Image Morphing
Colorization of gray-scale images relies on prior color information. Exa...
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07/28/2016
A Nonlocal Denoising Algorithm for Manifold-Valued Images Using Second Order Statistics
Nonlocal patch-based methods, in particular the Bayes' approach of Lebru...
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12/13/2014
