Theses

We are always looking for talented and motivated students who want to write a thesis or carry out a term project in Uncertainty Quantification, Scientific Computing or Numerical Analysis. As prerequisite you should have completed a course (e.g. MA5348, MA9804, MA9803) or seminar (Bachelor, Master) offered by the group (see teaching page). Please contact Prof. Ullmann by email for an appointment to discuss possible topics.

PhD Theses

2021

Schaden, Daniel: Variance reduction with multilevel estimators. Dissertation, 2021 mehr…
Wagner, Fabian: On efficient methods and error bounds for rare event estimation. Dissertation, 2021 mehr…

2019

Latz, Jonas: Exploring and exploiting hierarchies in Bayesian inverse problems. Dissertation, 2019 mehr…

Master's Theses

2022

Daniel Fischer: Galerkin Neural Networks. Masterarbeit, 2022 mehr…
Konstantin Althaus: Consensus-based rare event estimation. , 2022 mehr…
Laura Beckmann: Physics-informed Neural Networks in Bayesian Inversion. Masterarbeit, 2022 mehr…
Manuel Gehmeyr: Bayesian Reconstruction and Optimal Experimental Design for Multispectral Optoacoustic Tomography. Masterarbeit, 2022 mehr…
Tanja Wurdack: Physics-informed neural networks and finite differences augmented with neural networks for solving differential equations. Masterarbeit, 2022 mehr…

2021

Tobias Blindganser: Analysis of the Karhunen-Loève truncation error for rare event estimation. Masterarbeit, 2021 mehr…

2018

Fabian Wagner: Particle Methods for Deep Learning, Supervisor. Masterarbeit, 2018 mehr…
Sabrina Balzer: Gaussian process surrogates for Bayesian parameter identification in computational oncology. Masterarbeit, 2018 mehr…

2017

Marvin Eisenberger: Parameterized solution of Karhunen-Loeve Eigenproblems with Reduced Basis Methods in Uncertainty Quantification. Masterarbeit, 2017 mehr…

Bachelor's Theses

2022

Beatrix Rahnsch: Network-based inference for the prediction of the COVID-19 spread. Bachelorarbeit, 2022 mehr…
Lino Marschall: Chladni Plate - Eigenvalue Problem of the Biharmonic Operator. Bachelorarbeit, 2022 mehr…

2021

David Niederkofler: Multigrid Methods for the Approximate Solution of Partial Differential Equations. Bachelorarbeit, 2021 mehr…

2020

Tobias Neubauer: Hierarchical Neural Networks for Rare Event Estimation. Bachelorarbeit, 2020 mehr…
Vivien Wuwer: Stein Variational Gradient Descent for Rare Event Estimation. Bachelorarbeit, 2020 mehr…

2019

Christian Dietz: Iterative Solvers for Discretized PDEs. Bachelorarbeit, 2019 mehr…
Joshua Ekaputra: Approximation of Dynamical Systems with Neural Networks. Bachelorarbeit, 2019 mehr…
Medeea Horvat: Visual SLAM using artificial visual markers. Bachelorarbeit, 2019 mehr…
Samuel Amar: Adaptive Metropolis for Bayesian Inference in Crystallography. Bachelorarbeit, 2019 mehr…
Sarah Kreuzer: Efficient Implementation of the Ising Model and Image Denoising. Bachelorarbeit, 2019 mehr…

2018

Annabel Huber: Neural Networks as a Method for Solving ODEs. Bachelorarbeit, 2018 mehr…
Konstantin Riedl: On multilevel algorithms for the estimation of failure probabilities and rare event simulation. Bachelorarbeit, 2018 mehr…
Matthieu Bulté: Sequential Monte Carlo for time-dependent Bayesian Inverse Problems. Bachelorarbeit, 2018 mehr…