Dieses Bild zeigt Langer

Herr Dr. techn.

Andreas Langer

Research assistant
Institute of Applied Analysis and Numerical Simulation
Numerical Mathematics for High Performance Computing


+49 711 685-69317
+49 711 685-65507


Pfaffenwaldring 57
70569 Stuttgart
Raum: 7.155


  1. 2018

    1. Langer, A. Locally adaptive total variation for removing mixed Gaussian-impulse noise. International Journal of Computer Mathematics, 19.
    2. Langer, A. Overlapping domain decomposition methods for total variation denoising Retrieved from http://people.ricam.oeaw.ac.at/a.langer/publications/DDfTV_1preprint.pdf.
    3. Langer, A. Investigating the influence of box-constraints on the solution of a total variation model via an efficient primal-dual method. Journal of Imaging, 4, 1.
  2. 2017

    1. Langer, A. Automated Parameter Selection for Total Variation Minimization in Image Restoration. Journal of Mathematical Imaging and Vision, 57, 239--268.
    2. Langer, A. Automated Parameter Selection in the $L^1$-$L^2$-TV Model for Removing Gaussian Plus Impulse Noise. Inverse Problems, 33, 41.
    3. Alkämper, M., & Langer, A. Using DUNE-ACFem for Non-smooth Minimization of Bounded Variation Functions. Archive of Numerical Software, 5(1), 3--19.
    4. Hintermüller, Michael, Rautenberg, C. N., Wu, T., & Andreas Langer. Optimal Selection of the Regularization Function in a Weighted Total Variation Model. Part II: Algorithm, Its Analysis and Numerical Tests. Journal of Mathematical Imaging and Vision, 1--19.
    5. Hintermüller, Michael, Langer, A., Rautenberg, C. N., & Wu, T. Adaptive regularization for reconstruction from subsampled data. WIAS Preprint No. 2379 Retrieved from http://www.wias-berlin.de/preprint/2379/wias_preprints_2379.pdf.
  3. 2015

    1. Hintermüller, Michael, & Langer, A. Non-overlapping domain decomposition methods for dual total variation based image denoising. Journal of Scientific Computing, 62(2), 456--481.
  4. 2014

    1. Hintermüller, M, & Langer, A. Adaptive Regularization for Parseval Frames in Image Processing. SFB-Report No. 2014-014 Retrieved from http://people.ricam.oeaw.ac.at/a.langer/publications/SFB-Report-2014-014.pdf.
    2. Hintermüller, Michael, & Langer, A. Surrogate Functional Based Subspace Correction Methods for Image Processing. In Domain Decomposition Methods in Science and Engineering XXI (pp. 829--837). Springer.
  5. 2013

    1. Hintermüller, Michael, & Langer, A. Subspace Correction Methods for a Class of Nonsmooth and Nonadditive Convex Variational Problems with Mixed $L^1$/$L^2$ Data-Fidelity in Image Processing. SIAM Journal on Imaging Sciences, 6(4), 2134--2173.
    2. Langer, A., Osher, S., & Schönlieb, C.-B. Bregmanized domain decomposition for image restoration. Journal of Scientific Computing, 54(2), 549--576.
  6. 2012

    1. Fornasier, M., Kim, Y., Langer, A., & Schönlieb, C.-B. Wavelet Decomposition Method for $L_2$/TV-Image Deblurring. SIAM Journal on Imaging Sciences, 5(3), 857--885.
  7. 2010

    1. Fornasier, M., Langer, A., & Schönlieb, C.-B. A convergent overlapping domain decomposition method for total variation minimization. Numerische Mathematik, 116(4), 645--685.
  8. 2009

    1. Fornasier, M., Langer, A., & Schönlieb, C.-B. Domain decomposition methods for compressed sensing. In Proceedings of the International Conference of SampTA09 Retrieved from http://arxiv.org/abs/0902.0124.

Winter term 2018/19

  • Programmierkurs für den Bachelor

Summer term 2018

  • Numerical Methods for Differential Equations
  • Fortgeschrittene Analysis für SimTech 2

Winter term 2017/18

  • Seminar: Multifield Problems in Image Analysis and Visualization
  • Einführung in die Optimierung

Summer term 2017

  • Grundlagen inverser Probleme
  • Weiterführende Numerik partieller Differentialgleichungen

Winter term 2016/17

  • Einführung in die Optimierung
  • Seminar: Mathematische Probleme in der Bildbearbeitung

Summer term 2016

  • Höhere Mathematik 2 (Assistant)

Winter term 2015/16

  • Höhere Mathematik 3 (Assistant)

Summer term 2015

  • Numerische Mathematik 2 (Assistant)

Winter term 2014/15

  • Numerische Mathematik 1 (Assistant)

Summer term 2014

  • Numerische Mathematik 2 (Assistant)