Leon Bungert

Lehrstuhl für Angewandte Mathematik (Modellierung und Numerik)

The Infinity Laplacian Eigenvalue Problem: Reformulation and a Numerical Scheme (2024) Bozorgnia F, Bungert L, Tenbrinck D Journal article, Original article A Bregman Learning Framework for Sparse Neural Networks (2022) Bungert L, Roith T, Tenbrinck D, Burger M Journal article, Original article CLIP: Cheap Lipschitz Training of Neural Networks (2021) Bungert L, Raab R, Roith T, Schwinn L, Tenbrinck D Conference contribution, Conference Contribution Identifying untrustworthy predictions in neural networks by geometric gradient analysis (2021) Schwinn L, Nguyen A, Raab R, Bungert L, Tenbrinck D, Zanca D, Burger M, Eskofier B Conference contribution, Conference Contribution Robust Image Reconstruction with Misaligned Structural Information (2020) Bungert L, Ehrhardt MJ Journal article Variational regularisation for inverse problems with imperfect forward operators and general noise models (2020) Bungert L, Burger M, Korolev Y, Schönlieb CB Journal article Structural analysis of an L-infinity variational problem and relations to distance functions (2020) Bungert L, Korolev Y, Burger M Journal article Localization of Passive 3-D Coils as an Inverse Problem: Theoretical Analysis and a Numerical Method (2020) Doss M, Bungert L, Cichon D, Brauer H, Psiuk R Journal article Localization of Passive 3D-Coils as an Inverse Problem: Theoretical Analysis and a Numerical Method (2020) Doß M, Bungert L, Cichon D, Brauer H, Psiuk R Journal article Computing Nonlinear Eigenfunctions via Gradient Flow Extinction (2019) Bungert L, Burger M, Tenbrinck D Book chapter / Article in edited volumes