| Blind image fusion for hyperspectral imaging with the directional total variation L Bungert, DA Coomes, MJ Ehrhardt, J Rasch, R Reisenhofer, ... Inverse Problems 34 (4), 044003, 2018 | 74 | 2018 |
| CLIP: Cheap Lipschitz training of neural networks L Bungert, R Raab, T Roith, L Schwinn, D Tenbrinck International Conference on Scale Space and Variational Methods in Computer …, 2021 | 49 | 2021 |
| Nonlinear spectral decompositions by gradient flows of one-homogeneous functionals L Bungert, M Burger, A Chambolle, M Novaga Analysis & PDE 14 (3), 823-860, 2021 | 46 | 2021 |
| Asymptotic Profiles of Nonlinear Homogeneous Evolution Equations of Gradient Flow Type L Bungert, M Burger Journal of Evolution Equations, 2019 | 43 | 2019 |
| Continuum limit of Lipschitz learning on graphs T Roith, L Bungert Foundations of Computational Mathematics 23 (2), 393-431, 2023 | 38 | 2023 |
| A Bregman learning framework for sparse neural networks L Bungert, T Roith, D Tenbrinck, M Burger Journal of Machine Learning Research 23 (192), 1-43, 2022 | 34 | 2022 |
| Polarized consensus-based dynamics for optimization and sampling L Bungert, T Roith, P Wacker Mathematical Programming 211 (1), 125-155, 2025 | 33 | 2025 |
| Uniform convergence rates for Lipschitz learning on graphs L Bungert, J Calder, T Roith IMA Journal of Numerical Analysis 43 (4), 2445-2495, 2023 | 31 | 2023 |
| The geometry of adversarial training in binary classification L Bungert, N García Trillos, R Murray Information and Inference: A Journal of the IMA 12 (2), 921-968, 2023 | 30 | 2023 |
| Robust image reconstruction with misaligned structural information L Bungert, MJ Ehrhardt IEEE Access 8, 222944-222955, 2020 | 27 | 2020 |
| Improving robustness against real-world and worst-case distribution shifts through decision region quantification L Schwinn, L Bungert, A Nguyen, R Raab, F Pulsmeyer, D Precup, ... International Conference on Machine Learning, 19434-19449, 2022 | 26 | 2022 |
| Eigenvalue problems in 𝐿^{∞}: optimality conditions, duality, and relations with optimal transport L Bungert, Y Korolev Communications of the American Mathematical Society 2 (08), 345-373, 2022 | 22 | 2022 |
| Solution paths of variational regularization methods for inverse problems L Bungert, M Burger Inverse Problems 35 (10), 105012, 2019 | 22 | 2019 |
| Gamma-convergence of a nonlocal perimeter arising in adversarial machine learning L Bungert, K Stinson Calculus of Variations and Partial Differential Equations 63 (5), 114, 2024 | 20 | 2024 |
| Variational regularisation for inverse problems with imperfect forward operators and general noise models L Bungert, M Burger, Y Korolev, CB Schönlieb Inverse Problems 36 (12), 125014, 2020 | 19 | 2020 |
| Computing nonlinear eigenfunctions via gradient flow extinction L Bungert, M Burger, D Tenbrinck International conference on scale space and variational methods in computer …, 2019 | 19 | 2019 |
| Identifying untrustworthy predictions in neural networks by geometric gradient analysis L Schwinn, A Nguyen, R Raab, L Bungert, D Tenbrinck, D Zanca, ... Uncertainty in Artificial Intelligence, 854-864, 2021 | 17 | 2021 |
| Structural analysis of an L-infinity variational problem and relations to distance functions L Bungert, Y Korolev, M Burger Pure and Applied Analysis 2 (3), 703-738, 2020 | 17 | 2020 |
| The Infinity Laplacian Eigenvalue Problem: Reformulation and a Numerical Scheme F Bozorgnia, L Bungert, D Tenbrinck Journal of Scientific Computing 98 (2), 40, 2024 | 16 | 2024 |
| Nonlinear power method for computing eigenvectors of proximal operators and neural networks L Bungert, E Hait-Fraenkel, N Papadakis, G Gilboa SIAM Journal on Imaging Sciences 14 (3), 1114-1148, 2021 | 13 | 2021 |
Martin BurgerDeutsches Elektronen-Synchrotron DESY und Universität HamburgVerified email at uni-hamburg.de
