Leon Bungert

CoRR, June, 2025

Polarized consensus-based dynamics for optimization and sampling.

[BibT_eX]

[DOI]

Math. Program., May, 2025

MirrorCBO: A consensus-based optimization method in the spirit of mirror descent.

[BibT_eX]

[DOI]

CoRR, January, 2025

Book Review: Optimal Mass Transport on Euclidean Spaces.

[BibT_eX]

[DOI]

SIAM Rev., 2025

Meshless Shape Optimization Using Neural Networks and Partial Differential Equations on Graphs.

[BibT_eX]

[DOI]

Eloi Martinet

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2025

2024

The Infinity Laplacian Eigenvalue Problem: Reformulation and a Numerical Scheme.

[BibT_eX]

[DOI]

Farid Bozorgnia

Daniel Tenbrinck

J. Sci. Comput., February, 2024

Convergence rates for Poisson learning to a Poisson equation with measure data.

[BibT_eX]

[DOI]

CoRR, 2024

A mean curvature flow arising in adversarial training.

[BibT_eX]

[DOI]

Tim Laux

Kerrek Stinson

CoRR, 2024

2023

Continuum Limit of Lipschitz Learning on Graphs.

[BibT_eX]

[DOI]

Found. Comput. Math., April, 2023

Complete Deterministic Dynamics and Spectral Decomposition of the Linear Ensemble Kalman Inversion.

[BibT_eX]

[DOI]

SIAM/ASA J. Uncertain. Quantification, March, 2023

It begins with a boundary: A geometric view on probabilistically robust learning.

[BibT_eX]

[DOI]

Nicolás García Trillos

CoRR, 2023

2022

A Bregman Learning Framework for Sparse Neural Networks.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

Gamma-convergence of a nonlocal perimeter arising in adversarial machine learning.

[BibT_eX]

[DOI]

Kerrek Stinson

CoRR, 2022

Ratio convergence rates for Euclidean first-passage percolation: Applications to the graph infinity Laplacian.

[BibT_eX]

[DOI]

Jeff Calder

CoRR, 2022

Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

2021

Nonlinear Power Method for Computing Eigenvectors of Proximal Operators and Neural Networks.

[BibT_eX]

[DOI]

SIAM J. Imaging Sci., 2021

The Geometry of Adversarial Training in Binary Classification.

[BibT_eX]

[DOI]

Nicolás García Trillos

Ryan Murray

CoRR, 2021

Uniform Convergence Rates for Lipschitz Learning on Graphs.

[BibT_eX]

[DOI]

Jeff Calder

CoRR, 2021

Neural Architecture Search via Bregman Iterations.

[BibT_eX]

[DOI]

CoRR, 2021

Gradient Flows, Nonlinear Power Methods, and Computation of Nonlinear Eigenfunctions.

[BibT_eX]

[DOI]

Martin Burger

CoRR, 2021

Complete Dynamics and Spectral Decomposition of the Ensemble Kalman Inversion.

[BibT_eX]

[DOI]

CoRR, 2021

Identifying untrustworthy predictions in neural networks by geometric gradient analysis.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

CLIP: Cheap Lipschitz Training of Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2021

2020

Variational regularisation for inverse problems with imperfect forward operators and general noise models.

[BibT_eX]

[DOI]

Carola-Bibiane Schoenlieb

Martin Burger

Yury Korolev

CoRR, 2020

Robust Image Reconstruction With Misaligned Structural Information.

[BibT_eX]

[DOI]

Matthias J. Ehrhardt

IEEE Access, 2020

2019

Computing Nonlinear Eigenfunctions via Gradient Flow Extinction.

[BibT_eX]

[DOI]

Martin Burger

Daniel Tenbrinck

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2019

2018

Comparison of two local discontinuous Galerkin formulations for the subjective surfaces problem.

[BibT_eX]

[DOI]

Vadym Aizinger

Michael Fried

Comput. Vis. Sci., 2018

2017

A Discontinuous Galerkin Method for the Subjective Surfaces Problem.

[BibT_eX]

[DOI]