Teaching

Information for Students

• The office hours of Prof. Klein are by appointment.
• For details regarding available Master's Theses, please see the corresponding section below.

• Lectures (Winter Semester 2024/2025)

  Advanced Bayesian Data Analysis (5 ECTS)

  Every second week, the following course components take place

  Lecture: Tuesdays 11:30 - 13:00 (50.19, Seminarraum 1), Wednesdays 09:45 - 11:15 (50.28, Seminarraum 2) Tutorial: Tuesdays 09:45 - 11:15 (50.19, Seminarraum 5)

  ILIAS

  More details follow in the first session (22.10.2024), where no Tutorial takes place.

• Master Theses

  We offer Master theses at the intersection of statistics and machine learning. Please see below for titles of available theses in these areas. If you are interested in one of these projects and fulfill the requirements laid out in our thesis guidelines, please contact us for more details.

  • Understanding And Implementing Predictive Information Criteria For Bayesian Models
  • Asymptotic Behaviour Of The Posterior In Overfitted (Deep) Mixture Models
  • Posterior Concentration Rates For Bayesian High-Dimensional Sparse Additive Models
  • Uncertainty Quantification For Deep Learning
  • Using Stacking To Average Distributional Regression Models
  • Distributional Joint Modelling
  • Approximations Of Normalizing Constants In Doubly-Intractable Likelihoods
  • Measuring The Explained Variance In Structured Additive Distributional Regression
  • Comparisons And Implementation Of Non-Local Shrinkage Priors
  • Admissible Learning Algorithms
  • Approximated Bayesian Multivariate Spatial Factor Analysis
  • A Scalable Joint Model Of Longitudinal And Survival Data With Long-Term Survivors
  • Exact Likelihood Inference In Joint Modelling Settings
  • Targeted Sampling Based On Epistemic Uncertainty For Improving Predictive Performance Of Dl Tasks In The Case Of Costly Data Acquisition
  • Uncertainty Quantification For Complex-Valued Deep Neural Networks
  • Improved Variational Approximations
  • Non-Gaussian Regression Copulas
  • Variational Inference for Distributional Regression

  Theses with External Collaborators

  • Gaussian Processes and semiparametric modelling for Bayesian Optimization: a benchmark study (in cooperation with Prof. Katja Ickstadt)
  • Analysis of routine data from outpatient medical care (in cooperation with the University of Lübeck)

  
  

  A selection of completed theses at the chair can be found below.

  Master Theses

  • Analyzing Heat and Experienced Racial Segregation using Large-Scale Foot Traffic Data
  • A Python Implementation for the Structural Topic Model
  • Optimierung der Kraftwerkssteuerung mittel Reinforcement Learning unter Einsatz von kurzfristigen Ausgleichsenergiepreiseprognosen
  • Including Deep Neural Network Architectures into Multistage Intensity Models: An Application to Credit Risks
  • MultiFlags and LatentFlags: A Probabilistic Framework for Size Advice in Fashion E-Commerce
  • Interpretable Modelling of ICU Patients Remaining Length-of-Stay Distribution using Tabular Patient Data, Clinical Notes and Irregularly Spaced Clinical Measurements
  • Using Variational Inference to Estimate Structred Additive Distributional Regression Models
  • Elastic Full Procluster Means for Sparse and Irregular Curves
  • Reconstructing Multivariate Functional Data with Medical Applications
  • Investment Constraints in Southern Europe: A Spatial Econometric Analysis of World Bank Enterprise Surveys

  Bachelor Theses

  • Application of Regression Trees on Compositional Data Using European Parliament Election Results
  • Die Modellierung der COVID-19 Fallzahlen in Abhängigkeit von Strukturdaten zu Wetter und Bevölkerung in Berlin
  • Vergleich von Vorhersagemodellen zu Stornierungen von Hotelbuchungen

  Show completed theses Collapse completed theses