Bruna, M., Burger, M., & Wit, O. de. (2025). Lane formation and aggregation spots in a model of ants. SIAM Journal on Applied Dynamical Systems.

Burger, M., Erbar, M., Hoffmann, F., Matthes, D., & Schlichting, A. (2025). Covariance-modulated optimal transport and gradient flows. Archive for Rational Mechanics and Analysis.

Burger, M., Loy, N., & Rossi, A. (2025). Asymptotic and Stability Analysis of Kinetic Models for Opinion Formation on Networks: An Allen�Cahn Approach. SIAM Journal on Applied Dynamical Systems.

Fazeny, A., Burger, M., & Pietschmann, J.-F. (2025). Optimal transport on gas networks. European Journal of Applied Mathematics.

Shi, K., & Burger, M. (2025). Hypergraph p-laplacian regularization on point clouds for data interpolation. Nonlinear Analysis.

Shi, K., & Burger, M. (2025). Hypergraph p-Laplacian Equations for Data Interpolation and Semi-supervised Learning. Journal of Scientific Computing.

Burger, M., Kabri, S., Korolev, Y., Roith, T., & Weigand, L. (2025). Analysis of mean-field models arising from self-attention dynamics in transformer architectures with layer normalization. arXiv Preprint arXiv:2501.03096.

Inverse Problems on Large Scales: Mathematical Modelling and Computational Methods. (2024). De Gruyter. https://doi.org/10.1515/9783111357270

Ran, Y., Guo, Z., Li, J., Li, Y., Burger, M., & Wu, B. (2024). A Tunable Despeckling Neural Network Stabilized via Diffusion Equation (arXiv:2411.15921). arXiv. https://doi.org/10.48550/arXiv.2411.15921

Shi, K., & Burger, M. (2024). Hypergraph $p$-Laplacian equations for data interpolation and semi-supervised learning (arXiv:2411.12601). arXiv. https://doi.org/10.48550/arXiv.2411.12601

Burger, M., & Kabri, S. (2024). Learned regularization for inverse problems. In T. A. Bubba (Ed.), Data-driven Models in Inverse Problems (pp. 39–72). De Gruyter. https://doi.org/10.1515/9783111251233-002

Burger, M., Ehrhardt, M. J., Kuger, L., & Weigand, L. (2024). Analysis of Primal-Dual Langevin Algorithms (arXiv:2405.18098). arXiv. https://doi.org/10.48550/arXiv.2405.18098

Deidda, P., Burger, M., Putti, M., & Tudisco, F. (2024). The graph $\infty$-Laplacian eigenvalue problem (arXiv:2410.19666). arXiv. https://doi.org/10.48550/arXiv.2410.19666

Learning in Image Reconstruction: A Cautionary Tale | SIAM. (2024, October 1). Society for Industrial and Applied Mathematics. https://www.siam.org/publications/siam-news/articles/learning-in-image-reconstruction-a-cautionary-tale/

Ehrhardt, M. J., Kuger, L., & Schönlieb, C.-B. (2024). Proximal Langevin Sampling With Inexact Proximal Mapping. SIAM Journal on Imaging Sciences, 17(3), 1729–1760. https://doi.org/10.1137/23M1593565

Bruna, M., Burger, M., & Wit, O. de. (2024). Lane formation and aggregation spots in a model of ants (arXiv:2401.15046). arXiv. https://doi.org/10.48550/arXiv.2401.15046

Fazeny, A., Tenbrinck, D., Lukin, K., & Burger, M. (2024). Hypergraph p-Laplacians and Scale Spaces. Journal of Mathematical Imaging and Vision, 66(4), 529–549. https://doi.org/10.1007/s10851-024-01183-0

Burger, M., Loy, N., & Rossi, A. (2024). Asymptotic and stability analysis of kinetic models for opinion formation on networks: an Allen-Cahn approach (arXiv:2407.03375). arXiv. https://doi.org/10.48550/arXiv.2407.03375

Burger, M., Schuster, T., & Wald, A. (2024). Ill-posedness of time-dependent inverse problems in Lebesgue-Bochner spaces. Inverse Problems, 40(8), 085008. https://doi.org/10.1088/1361-6420/ad5a35

Bailo, R., Barbaro, A., Gomes, S. N., Riedl, K., Roith, T., Totzeck, C., & Vaes, U. (2024). CBX: Python and Julia packages for consensus-based interacting particle methods. Journal of Open Source Software, 9(98), 6611. https://doi.org/10.21105/joss.06611

Weigand, L., Roith, T., & Burger, M. (2024). Adversarial flows: A gradient flow characterization of adversarial attacks (arXiv:2406.05376). arXiv. https://doi.org/10.48550/arXiv.2406.05376

Kabri, S., Auras, A., Riccio, D., Bauermeister, H., Benning, M., Moeller, M., & Burger, M. (2024). Convergent Data-Driven Regularizations for CT Reconstruction. Communications on Applied Mathematics and Computation, 6(2), 1342–1368. https://doi.org/10.1007/s42967-023-00333-2

Shi, K., & Burger, M. (2024). Hypergraph $p$-Laplacian regularization on point clouds for data interpolation (arXiv:2405.01109). arXiv. https://doi.org/10.48550/arXiv.2405.01109

Fazeny, A., Burger, M., & Pietschmann, J.-F. (2024). Optimal transport on gas networks (arXiv:2405.01698). arXiv. https://doi.org/10.48550/arXiv.2405.01698

Shi, K., & Burger, M. (2024). Continuum limit of $p$-biharmonic equations on graphs (arXiv:2404.19689). arXiv. https://doi.org/10.48550/arXiv.2404.19689

Bungert, L., Calder, J., & Roith, T. (2024). Ratio convergence rates for Euclidean first-passage percolation: Applications to the graph infinity Laplacian (arXiv:2210.09023). arXiv. https://doi.org/10.48550/arXiv.2210.09023

Brokman, J., Burger, M., & Gilboa, G. (2024). Spectral Total-Variation Processing of Shapes - Theory and Applications. ACM Transactions on Graphics. https://doi.org/10.1145/3641845

Roith, T. (2024). Consistency, Robustness and Sparsity for Learning Algorithms. https://open.fau.de/handle/openfau/30802

Bungert, L., Roith, T., & Wacker, P. (2023). Polarized consensus-based dynamics for optimization and sampling (arXiv:2211.05238). arXiv. https://doi.org/10.48550/arXiv.2211.05238

Burger, M., Schuster, T., & Wald, A. (2023). Ill-posedness of time-dependent inverse problems in Lebesgue-Bochner spaces (arXiv:2310.08600). arXiv. http://arxiv.org/abs/2310.08600

Burger, M., Kanzler, L., & Wolfram, M.-T. (2023). Boltzmann mean-field game model for knowledge growth: limits to learning and general utilities (arXiv:2209.04677). arXiv. https://doi.org/10.48550/arXiv.2209.04677

Burger, M., & Esposito, A. (2023). Porous medium equation and cross-diffusion systems as limit of nonlocal interaction. Nonlinear Analysis, 235, 113347. https://doi.org/10.1016/j.na.2023.113347

Burger, M., & Schulz, S. (2023). Well-posedness and stationary states for a crowded active Brownian system with size-exclusion (arXiv:2309.17326). arXiv. https://doi.org/10.48550/arXiv.2309.17326

Burger, M., Humpert, I., & Pietschmann, J.-F. (2023). Dynamic Optimal Transport on Networks. ESAIM: Control, Optimisation and Calculus of Variations, 29, 54. https://doi.org/10.1051/cocv/2023027

Fazeny, A., Tenbrinck, D., & Burger, M. (2023). Hypergraph p-Laplacians, Scale Spaces, and Information Flow in Networks. In L. Calatroni, M. Donatelli, S. Morigi, M. Prato, & M. Santacesaria (Eds.), Scale Space and Variational Methods in Computer Vision (pp. 677–690). Springer International Publishing. https://doi.org/10.1007/978-3-031-31975-4_52

Kabri, S., Roith, T., Tenbrinck, D., & Burger, M. (2023). Resolution-Invariant Image Classification Based on Fourier Neural Operators. In L. Calatroni, M. Donatelli, S. Morigi, M. Prato, & M. Santacesaria (Eds.), Scale Space and Variational Methods in Computer Vision (pp. 236–249). Springer International Publishing. https://doi.org/10.1007/978-3-031-31975-4_18

Kabri, S., Auras, A., Riccio, D., Bauermeister, H., Benning, M., Moeller, M., & Burger, M. (2022). Convergent Data-driven Regularizations for CT Reconstruction (arXiv:2212.07786). arXiv. https://doi.org/10.48550/arXiv.2212.07786

Burger, M. (2021). Variational Regularization in Inverse Problems and Machine Learning (arXiv:2112.04591). arXiv. https://doi.org/10.48550/arXiv.2112.04591

Burger, M., Jansen, S., Hölzer, K., Kaden, T., Kuger, L., Lösch, H., Petrak, S., Rieger, T., & Schönmuth, T. (n.d.). Multiple scatter correction for single plane Compton camera imaging in nuclear decommissioning. PAMM, n/a(n/a), e202300281. https://doi.org/10.1002/pamm.202300281

Sharp interface analysis of a diffuse interface model for cell blebbing with linker dynamics - Nöldner - 2023 - ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik - Wiley Online Library. (n.d.). Retrieved January 29, 2024, from https://onlinelibrary.wiley.com/doi/10.1002/zamm.202300101