Blind Image Fusion for Hyperspectral Imaging with the Directional Total Variation. - Leon Bungert; David A. Coomes; Matthias J. Ehrhardt; Jennifer Rasch; Rafael Reisenhofer; Carola-Bibiane Schönlieb (CoRR, 2017)

A Discontinuous Galerkin Method for the Subjective Surfaces Problem. - Leon Bungert; Vadym Aizinger; Michael Fried (J. Math. Imaging Vis., 2017)

Comparison of two local discontinuous Galerkin formulations for the subjective surfaces problem. - Vadym Aizinger; Leon Bungert; Michael Fried (Comput. Vis. Sci., 2018)

Computing Nonlinear Eigenfunctions via Gradient Flow Extinction. - Leon Bungert; Martin Burger 001; Daniel Tenbrinck (SSVM, 2019)

Robust Image Reconstruction With Misaligned Structural Information. - Leon Bungert; Matthias J. Ehrhardt (IEEE Access, 2020)

Variational regularisation for inverse problems with imperfect forward operators and general noise models. - Leon Bungert; Martin Burger 001; Yury Korolev; Carola-Bibiane Schoenlieb (CoRR, 2020)

CLIP: Cheap Lipschitz Training of Neural Networks. - Leon Bungert; René Raab; Tim Roith; Leo Schwinn; Daniel Tenbrinck (SSVM, 2021)

Identifying untrustworthy predictions in neural networks by geometric gradient analysis. - Leo Schwinn; An Nguyen; René Raab; Leon Bungert; Daniel Tenbrinck; Dario Zanca; Martin Burger 001; Björn M. Eskofier (UAI, 2021)

Complete Dynamics and Spectral Decomposition of the Ensemble Kalman Inversion. - Leon Bungert; Philipp Wacker (CoRR, 2021)

Gradient Flows, Nonlinear Power Methods, and Computation of Nonlinear Eigenfunctions. - Leon Bungert; Martin Burger 001 (CoRR, 2021)

Neural Architecture Search via Bregman Iterations. - Leon Bungert; Tim Roith; Daniel Tenbrinck; Martin Burger 001 (CoRR, 2021)

Uniform Convergence Rates for Lipschitz Learning on Graphs. - Leon Bungert; Jeff Calder; Tim Roith (CoRR, 2021)

The Geometry of Adversarial Training in Binary Classification. - Leon Bungert; Nicolás García Trillos; Ryan Murray 001 (CoRR, 2021)

Nonlinear Power Method for Computing Eigenvectors of Proximal Operators and Neural Networks. - Leon Bungert; Ester Hait-Fraenkel; Nicolas Papadakis; Guy Gilboa (SIAM J. Imaging Sci., 2021)

Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification. - Leo Schwinn; Leon Bungert; An Nguyen; René Raab; Falk Pulsmeyer; Doina Precup; Bjoern M. Eskofier; Dario Zanca (ICML, 2022)

Ratio convergence rates for Euclidean first-passage percolation: Applications to the graph infinity Laplacian. - Leon Bungert; Jeff Calder; Tim Roith (CoRR, 2022)

Gamma-convergence of a nonlocal perimeter arising in adversarial machine learning. - Leon Bungert; Kerrek Stinson (CoRR, 2022)

A Bregman Learning Framework for Sparse Neural Networks. - Leon Bungert; Tim Roith; Daniel Tenbrinck; Martin Burger 001 (J. Mach. Learn. Res., 2022)

It begins with a boundary: A geometric view on probabilistically robust learning. - Leon Bungert; Nicolás García Trillos; Matt Jacobs; Daniel McKenzie; Dorde Nikolic; Qingsong Wang (CoRR, 2023)

Complete Deterministic Dynamics and Spectral Decomposition of the Linear Ensemble Kalman Inversion. - Leon Bungert; Philipp Wacker (SIAM/ASA J. Uncertain. Quantification, 2023)

Continuum Limit of Lipschitz Learning on Graphs. - Tim Roith; Leon Bungert (Found. Comput. Math., 2023)

A mean curvature flow arising in adversarial training. - Leon Bungert; Tim Laux; Kerrek Stinson (CoRR, 2024)

Convergence rates for Poisson learning to a Poisson equation with measure data. - Leon Bungert; Jeff Calder; Max Mihailescu; Kodjo Houssou; Amber Yuan (CoRR, 2024)

The Infinity Laplacian Eigenvalue Problem: Reformulation and a Numerical Scheme. - Farid Bozorgnia; Leon Bungert; Daniel Tenbrinck (J. Sci. Comput., 2024)

Meshless Shape Optimization Using Neural Networks and Partial Differential Equations on Graphs. - Eloi Martinet; Leon Bungert (SSVM (2), 2025)

Book Review: Optimal Mass Transport on Euclidean Spaces. - Leon Bungert (SIAM Rev., 2025)

MirrorCBO: A consensus-based optimization method in the spirit of mirror descent. - Leon Bungert; Franca Hoffmann; Dohyeon Kim; Tim Roith (CoRR, 2025)

Polarized consensus-based dynamics for optimization and sampling. - Leon Bungert; Tim Roith; Philipp Wacker (Math. Program., 2025)

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies. - Tim Roith; Leon Bungert; Philipp Wacker (CoRR, 2025)