research
∙
02/28/2023
Parametrizing Product Shape Manifolds by Composite Networks
Parametrizations of data manifolds in shape spaces can be computed using...
share
research
∙
08/22/2022
Learning Low Bending and Low Distortion Manifold Embeddings: Theory and Applications
Autoencoders, which consist of an encoder and a decoder, are widely used...
research
∙
12/17/2021
Dimension reduction, exact recovery, and error estimates for sparse reconstruction in phase space
An important theme in modern inverse problems is the reconstruction of t...
research
∙
04/27/2021
Learning low bending and low distortion manifold embeddings
Autoencoders are a widespread tool in machine learning to transform high...
research
∙
12/15/2020
Quartic L^p-convergence of cubic Riemannian splines
We prove quartic convergence of cubic spline interpolation for curves in...
research
∙
03/30/2020
An adaptive finite element approach for lifted branched transport problems
We consider so-called branched transport and variants thereof in two spa...
research
∙
12/16/2019
Consistent Curvature Approximation on Riemannian Shape Spaces
We describe how to approximate the Riemann curvature tensor as well as s...
research
∙
02/20/2019
Dynamic Cell Imaging in PET with Optimal Transport Regularization
We propose a novel dynamic image reconstruction method from PET listmode...
research
∙
10/18/2017
A Sinkhorn-Newton method for entropic optimal transport
We consider the entropic regularization of discretized optimal transport...
research
∙
01/08/2017
A Framework for Wasserstein-1-Type Metrics
We propose a unifying framework for generalising the Wasserstein-1 metri...
research
∙
12/24/2016
Joint denoising and distortion correction of atomic scale scanning transmission electron microscopy images
Nowadays, modern electron microscopes deliver images at atomic scale. Th...
research
∙
10/02/2012