Prof. Dr. Martin Burger

Thomson Researcher ID: D-9928-2012


Lehrstuhl für Angewandte Mathematik (Modellierung und Numerik)

Awards / Honours

2014 : ERC Consolidator Grant
2009 : Calderón-Preis
1999 : Preis für Besondere Studentische Leistungen 1999

Project lead

PPP Frankreich 2019 Phase I
Prof. Dr. Martin Burger
(01/01/2019 - 31/12/2020)

(Nonlocal Methods for Arbitrary Data Sources):
NoMADS: Nonlocal Methods for Arbitrary Data Sources
Prof. Dr. Martin Burger
(01/10/2018 - 28/02/2022)

MED4D: "Verbundprojekt MED4D: Dynamische Medizinische Bildgebung: Modellierung und Analyse medizinischer Daten für verbesserte Diagnose, Überwachung und Arzneimittelentwicklung"
Prof. Dr. Martin Burger
(01/12/2016 - 30/11/2019)

DAAD Exchange Service: PPP Finnland 2017: Bayesian Inverse Problems in Banach Space
Prof. Dr. Martin Burger
(25/01/2015 - 31/12/2017)

LifeInverse: Variational Methods for Dynamic Inverse Problems in the Life Sciences
Prof. Dr. Martin Burger
(01/03/2014 - 28/02/2019)

Project member

IntComSin: Interfaces, complex structures, and singular limits in continuum mechanics
Prof. Dr. Günther Grün
(01/04/2018 - 30/09/2022)

Other Research Activities

Editorship of a scientific journal / series
Prof. Dr. Martin Burger
Editorial head - European Journal of Applied Mathematics (ISSN: 1469-4425)

Publications (Download BibTeX)

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Bungert, L., & Burger, M. (2019). Asymptotic Profiles of Nonlinear Homogeneous Evolution Equations of Gradient Flow Type. (Unpublished, Submitted).
Burger, M., Korolev, Y., Schönlieb, C.B., & Stollenwerk, C. (2019). A Total Variation Based Regularizer Promoting Piecewise-Lipschitz Reconstructions. In Jan Lellmann, Jan Modersitzki, Martin Burger (Eds.), Lecture Notes in Computer Science (pp. 485-497). Hofgeismar, DE: Springer Verlag.
Bungert, L., Burger, M., & Tenbrinck, D. (2019). Computing Nonlinear Eigenfunctions via Gradient Flow Extinction. In Scale Space and Variational Methods in Computer Vision - 7th International Conference, SSVM 2019, Proceedings. (pp. 291-302). Springer Verlag.
Burger, M., Korolev, Y., & Rasch, J. (2019). Convergence rates and structure of solutions of inverse problems with imperfect forward models. Inverse Problems, 35(2).
Burger, M., Föcke, J., Nickel, L., Jung, P., & Augustin, S. (2019). Reconstruction Methods in THz Single-Pixel Imaging. In Holger Boche, Giuseppe Caire, Robert Calderbank, Gitta Kutyniok, Rudolf Mathar, Philipp Petersen (Eds.), Compressed Sensing and Its Applications. (pp. 263-290). Springer International Publishing.
Bungert, L., & Burger, M. (2019). Solution paths of variational regularization methods for inverse problems. Inverse Problems.
Burger, M. (2018). A Variational Model for Joint Motion Estimation and Image Reconstruction. Siam Journal on Imaging Sciences, 11(1), 94-128.
Burger, M. (2018). Dynamic inverse problems: modelling-regularization-numerics Preface. Inverse Problems, 34(4).
Burger, M. (2018). Dynamic MRI reconstruction from undersampled data with an anatomical prescan. Inverse Problems, 34(7).
Burger, M. (2018). Dynamic SPECT reconstruction with temporal edge correlation. Inverse Problems, 34(1).

Last updated on 2019-22-01 at 17:51