Uncertainty Quantification in Inverse Problems: Bayesian inversion, Markov chain Monte Carlo sampling, dimension reduction techniques, computational aspects

  • Applications: Marine biogeochemistry, porous media



6. M. TP., D. Bittner, S. Mattis, G. Chiogna, and B. Wohlmuth, Bayesian calibration and sensitivity analysis for a karst aquifer model using active subspaces, 2019 – arXiv

5. D. Bittner, M. TP., S. Mattis, B. Wohlmuth, and G. Chiogna, On the relationship between parameters and discharge data for a lumped karst aquifer model, 2018 – arXiv

4. M. TP., A probabilistic framework for approximating functions in active subspaces, 2018 – arXiv


3. M. TP., S. Mattis, S. Gupta, C. Deusner, and B. Wohlmuth. Efficient parameter estimation for a methane hydrate model with active subspaces. Comput Geosci (2019) 23:355–372. – journal (full-text view-only), arXiv


2. Master thesis. Brownian Motion and the Dirichlet Problem, Ludwig-Maximilians-Universität München (LMU) – pdf


1. Bachelor thesis. N.V. Krylov’s Proof of the de Moivre-Laplace Theorem, University of Applied Sciences Munich (HM) – pdf

Talks, Conferences, etc.

2. M2 Oberseminar, Active subspaces for Bayesian inversion, Application to a methane hydrate model, Garching, 02.03.2018 (post, slides)
1. FrontUQ (Frontiers of Uncertainty Quantification in Engineering), Munich, 06.09.-08.09.2017