Marc Schmidlin


Doktorand (Philosophisch-Naturwissenschaftliche Fakultät)

I was a PhD student in Professor Helmut Harbrecht's Computational Mathematics research group.

Refereed Articles

  1. H. Harbrecht, V. Karnaev, and M. Schmidlin.
    Quantifying domain uncertainty in linear elasticity.
    SIAM/ASA J. Uncertain. Quantif., 12(2):503523, 2024.
  2. H. Harbrecht, M. Schmidlin, and Ch. Schwab.
    The Gevrey class implicit mapping theorem with application to UQ of semilinear elliptic PDEs.
    Math. Mod. Meth. Appl. Sci., 34(5):881–917, 2024.
  3. L.N. Felber, H. Harbrecht, and M. Schmidlin.
    Identification of sparsely representable diffusion parameters in elliptic problems.
    SIAM J. Imaging Sci., 17:1:61–90, 2024.
  4. S. Ben Bader, H. Harbrecht, R. Krause, M. Multerer, A. Quaglino, and M. Schmidlin.
    Space-time multilevel quadrature methods and their application for cardiac electrophysiology.
    SIAM/ASA J. Uncertain. Quantif., 11(4):1329–1356, 2023.
  5. H. Harbrecht and M. Schmidlin.
    Multilevel quadrature for elliptic problems on random domains by the coupling of FEM and BEM.
    Stoch. Partial Differ. Equ. Anal. Comput., 10:1619–1650, 2022.
  6. H. Harbrecht and M. Schmidlin.
    Multilevel methods for uncertainty quantification of elliptic PDEs with random anisotropic diffusion.
    Stoch. Partial Differ. Equ. Anal. Comput., 8(1):54–81, 2020.
  7. H. Harbrecht, M. Peters, and M. Schmidlin.
    Uncertainty quantification for PDEs with anisotropic random diffusion.
    SIAM J. Numer. Anal., 55(2):1002–1023, 2017.

Theses

  1. M. Schmidlin.
    Regularity analysis for semilinear elliptic PDEs with random data.
    PhD Thesis, University of Basel, 2024. doi: 10.5451/unibas-ep96377
  2. M. Schmidlin.
    Uncertainty Quantification for PDEs with Anisotropic Random Diffusion.
    Master’s Thesis, University of Basel, 2016.

Teaching

as a PhD student
FS21Einführung in die Numerik
HS20Numerik der Differentialgleichungen
FS20Integralgleichungen und Randelementmethode
HS19Numerik der partiellen Differentialgleichungen
FS19Projekt: Einführung in die Numerik
HS18Numerik der Differentialgleichungen
FS18Optimale Steuerung partieller Differentialgleichungen
HS17Numerik der partiellen Differentialgleichungen
FS17Einführung in die Numerik
HS16Einführung in die Statistik

 

as a student
FS16Algorithmische Mathematik: Graphen & Anwendungen
HS15Einführung in die Statistik
FS15Praktikum II
Computer Grafik
HS14Mathematische Methoden I
FS14Lineare Algebra II
HS13Mathematische Methoden I