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Bachelor's and Master's theses

I supervise theoretical, computational and applied theses in probability theory and statistics. Topics are usually related to random objects in Euclidean space. For a Master’s thesis students are required to have attended at least two parts of my lecture cycle Spatial Stochastics. This can be partly replaced by self-study from the lecture notes or by giving a good talk in a relevant seminar or oberseminar.

Below is a list of theses I have supervised. The names of the students have been omitted due to <add you favorite adjective here> European data protection laws. If you are the author of one of the theses below, I’m more than happy to add your name to your work (and possibly a link) if you give me explicit permission to do so.

Former M.Sc. topics

  • Iterative Boltzmann Inversion — A spatial statistics perspective (2023)
  • Theory for Hamiltonian MCMC algorithms for Gibbs processes (2023)
  • The Implementation of a Risk Analysis in the Reinsurance Sector using Copulas (2022); joint supervision with Prof. Michael Fröhlich
  • Structural Inference for Temporal Knowledge Graphs: a Deep Learning Method and a Stochastic Theory Framework (2022)
  • Pricing Approaches for the Insurance Division Aviation in Primary Insurance and Reinsurance (2022); joint supervision with Prof. Michael Fröhlich
  • Spatial Modelling of Gaussian Markov Random Fields using INLA and SPDEs (2021)
  • Uniqueness of Gibbs Measures: Sufficient Conditions (2021)
  • Estimation of Photovoltaic-Generated power: Convolutional Neural Network vs Kriging (2021)
  • Varianzanalyse in euklidischen und nichteuklidischen metrischen Räumen (2021)
  • Wasserstein Learning for Generative Point Process Models (2020)
  • Uniqueness of Gibbs measures via Disagreement Percolation (2020)
  • Binned Estimation of the Pair Correlation Function and Iterative Boltzmann Inversion (2020)
  • A Probabilistic Look at Mutual Information with Application to Point Process (2017)
  • Selective Importance Sampling for Computing the Maximum Likelihood Estimator in Point Process Models (2017)
  • Convergence Rates for Point Processes Thinned by Logit-Gaussian Random Fields (2016)
  • Maximum-Likelihood-Schätzung von exponentiellen Familien von stochastischen Prozessen (2016)
  • Maximum Likelihood Estimation for Spatial Point Processes using Monte Carlo Methods (2016)
  • Statistical Inference of Linear Birth-And-Death Processes (2015)
  • Konvergenzgeschwindigkeit für Markov-Chain Monte Carlo (2015)
  • Tests auf Unabhängigkeit zwischen Punkten und Marken (2015)
  • Thinning of Point Processes by [0,1]-Transformed Gaussian Random Fields (2014)
  • Additivity and Ortho-Additivity in Gaussian Random Fields (2013); joint supervision with Prof. David Ginsbourger

Former B.Sc. topics

  • Noisy Hamiltonian Monte Carlo with an application for point processes (2023)
  • Maximum Likelihood Estimation for Hawkes Processes and Real Data Application (2022)
  • Entrywise Relative Error Bounds for the Stationary Distribution of Perturbed Markov Chains on a Finite State Space. (2022)
  • Second Order Moment Measures of Point Processes (2022)
  • Obere Schranken bei der Bewertung von Stoploss-Verträgen in der Rückversicherung (2022); gemeinsame Betreuung mit Prof. Michael Fröhlich
  • Statistical Analysis of Simulation Algorithms for Finite Random Fields — with a Focus on the Swendsen-Wang Algorithm for the Ising Model (2022)
  • Sequential Monte Carlo Methods and Their Applications in Stock Markets (2022)
  • Comparison of Metropolis Chain and Glauber Dynamics for Proper q-Colorings on a Graph (2021)
  • Das Tobit-Modell: Methodische Anwendungen und Vergleiche zu linearen Regressionen (2021)
  • Markov-Ketten mit allgemeinem Zustandsraum (2021)
  • A comparison between Metropolis–Hastings and Hamiltonian Monte Carlo (2020)
  • Vorhersage im Besag-York-Mollié-Modell (2018)
  • Spline-Regression (2018)
  • Nichtparametrische Regression - Kernregression und lokale Polynome (2018)
  • Theorie und Simulation von Gaußschen Markov-Zufallsfeldern (2018)
  • Comparison of Logistic Regression and Maximum Pseudolikelihood for Spatial Point Processes (2017)
  • Metropolis-Hastings Algorithms for Spatial Point Processes (2016)
  • A Geometry-Based Approach for Solving the Transportation Problem with Euclidean Cost (2016)
  • A Comprehensive Overview of Linear Birth-and-Death Processes with an Outlook to the Non-Linear Case (2015)
  • Limit Behaviour of Discrete Models in Financial Mathematics (2015)
  • Gaußsche Zufallsfelder: Differenzierbarkeit von Pfaden (2015)
  • Shuffling Measures and the Total Variation Distance to a Perfectly Randomized Deck of Cards (2015)
  • Numerical Computation of L2-Wasserstein Distance Between Images (2014)
  • Erwartete Treffzeiten in Markovketten und deren Anwendung auf Glücksspiele mit Sicherungsoption (2013)