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20152025
most citedNon-constant functions with zero nonlocal gradient and their role in nonlocal Neumann-type problems

1 citations · 2 across the 12 of their papers we have counts for

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math.AP2025

Local boundary conditions in nonlocal hyperelasticity via heterogeneous horizons

Carolin Kreisbeck, Hidde Schönberger

In this paper, we consider a class of variational problems with integral functionals involving nonlocal gradients. These models have been recently proposed as refinements of classi…

math.AP2024

-convergence involving nonlocal gradients with varying horizon: Recovery of local and fractional models

Javier Cueto, Carolin Kreisbeck, Hidde Schönberger

This work revolves around the rigorous asymptotic analysis of models in nonlocal hyperelasticity. The corresponding variational problems involve integral functionals depending on n…

math.AP2024

Characterizing BV- and BD-ellipticity for a class of positively 1-homogeneous surface energy densities

Dominik Engl, Carolin Kreisbeck, Marco Morandotti

Lower semicontinuity of surface energies in integral form is known to be equivalent to BV-ellipticity of the surface density. In this paper, we prove that BV-ellipticity coincides…

math.AP20241 cited

Non-constant functions with zero nonlocal gradient and their role in nonlocal Neumann-type problems

Carolin Kreisbeck, Hidde Schönberger

This work revolves around properties and applications of functions whose nonlocal gradient, or more precisely, finite-horizon fractional gradient, vanishes. Surprisingly, in contra…

math.AP2023

A variational perspective on auxetic metamaterials of checkerboard-type

Wolf-Patrick Düll, Dominik Engl, Carolin Kreisbeck

The main result of this work is a homogenization theorem via variational convergence for elastic materials with stiff checkerboard-type heterogeneities under the assumptions of phy…

math.AP2022

Structural changes in nonlocal denoising models arising through bi-level parameter learning

Elisa Davoli, Rita Ferreira, Carolin Kreisbeck +1

We introduce a unified framework based on bi-level optimization schemes to deal with parameter learning in the context of image processing. The goal is to identify the optimal regu…