This paper studies the discretization of a homogenization and dimension
...
Parametrizations of data manifolds in shape spaces can be computed using...
This paper investigates a time discrete variational model for splines in...
Autoencoders, which consist of an encoder and a decoder, are widely used...
In this paper, a two-scale approach for elastic shape optimization of
fi...
In this paper, the numerical approximation of isometric deformations of ...
This paper investigates a variational model for splines in the image
met...
Autoencoders are a widespread tool in machine learning to transform
high...
We consider pessimistic bilevel stochastic programs in which the followe...
This paper investigates a discretization scheme for mean curvature motio...
This paper investigates the optimal distribution of hard and soft materi...
This paper investigates the optimal distribution of hard and soft materi...
We describe how to approximate the Riemann curvature tensor as well as
s...
We study the geometry of needle-shaped domains in shape-memory alloys.
N...
This paper combines image metamorphosis with deep features. To this end,...
Geometric optimization problems are at the core of many applications in
...
Brain shift, i.e. the change in configuration of the brain after opening...
Based on a local approximation of the Riemannian distance on a manifold ...