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Humboldt-Universität zu Berlin - Statistics

Chair of Statistics - Final theses

If you are interested in writing your thesis at the Chair of Statistics, please contact us for more details.

 

Useful links:

 

Student theses:

Author Title Supervisor

2021

Jost von Petersdorff-Campen Copula Regression for Discrete Data – An Application to Covid-19 Nadja Klein
Chris Kolb Application of Deep Distributional Regression to the Geospatial Distribution of Neglected Tropical Disease Vectors Nadja Klein
Per Joachims Uncertainty Quantification with Bayesian Neural Networks Nadja Klein
Malgorzata Olesiewicz Modelling of Missing not at Random Corporate Emissions Data for Sustainable Investment Sonja Greven
Clara Hoffmann Marginally Calibrated Posterior Densities for End-to-End Learning in Autonomous Driving Nadja Klein
Michael Schimpke Sentiment-Optimised Translation: An Approach for Multilingual Sealing of Pre-Trained Sentiment Classifiers Nadja Klein
Jakub Kondek Classification of Empathic and Non-Empathic Emails using Prototypical Networks Nadja Klein
Silvia Ventoruzzo On the Role of Weather in Predicting Online Sales of Different Product Categories Nadja Klein
Safiul Alom Uncertainty in Machine-Learning-based E-Mail Classification for Improved Customer Service Nadja Klein
Lukas Mödl The RODEO Approach for Nonparametric Density Estimation Nadja Klein
2020    
Anna Elisabeth Riha Hyperpriorsensitivity of Bayesian Wrapped Gaussian Processes with an Application to Wind Data Nadja Klein
Aaron Burgemeister Benchmarking Different Machine Learning Methods Against Logistic Regression in Credit Scoring Sonja Greven
Xiaoji Du Analysis of a Restaurant Database of 31 European Cities Sonja Greven
Jil Kollmus-Heege

Dynamic Prediction in Flexible Bayesian Additive Joint Models

Sonja Greven
Sisi Huang An Image Classification Tool of Wikimedia Commons Sonja Greven
Thomas Siskos Career Recommendations using Supervised Latent Dirichlet Allocation Sonja Greven
Kang Yang Deep Generalised Additive Regression Models for Location, Scale and Shape Nadja Klein
Paulina Kurowska Bayesian Variable Selection Approach in Additive Quantile Regression Nadja Klein
2019
Yinan Wu Bayesian Adaptive Lasso for Zero Inflated Count Model and Overdispersion Nadja Klein
Jerome Bau Context-aware Sentence Generation from Keywords Nadja Klein
Lukas Kemkes Comparison and Combination of Extractive and Abstractive Techniques for Machine Text Summarization Nadja Klein
Andrii Zakharov Development of a Customer Insolvency Prediction Model following the Cross-Industry Standard Process for Data Mining (CRISP-DM) Nadja Klein

 

Selected Theses:

Bachelor Theses

  • Regressionsmodelle und Hauptkomponentenanalyse für Billard-Bewegungstrajektorien (2019)
  • Classification of input devices using cursor trajectories (2017)
  • Funktions-auf-Skalar-Regression für Zellchipdaten (2015)
  • The Correlation Coefficient as a Measure of Similarity for Thermal Images in Medicine (2014)
  • Vergleich von Selektionskriterien für die Anzahl funktionaler Hauptkomponenten (2011)

 

Master Theses

  • A comparison of different approaches to the joint modelling of longitudinal and time-to-event outcomes (2019)
  • Multivariate functional regression models (2018)
  • Boosting flexible joint models for longitudinal and time-to-event data with medical applications
    (2018)
  • Clustering räumlicher Kurven zur Identifikation von Laufmustern bei Hypermarathonläufern (2017)
  • Joint modelling of longitudinal biomarker measurements and time-to-event with an application in
    patients with congestive heart failure (2017)
  • Multivariate Functional Principal Component Regression for Image Data with application to
    Neuroimaging (2017)
  • Elastic Registration and Functional Principal Component Analysis of Curves in 1D and 2D (2017)
  • Boosting Generalized Additive Models for Location, Scale and Shape (GAMLSS) for Functional Data
    (2016)
  • Joint modelling of multiple longitudinal islet autoantibody profiles and the onset of type 1 diabetes
    (2015; Kooperation mit dem Helmholtz-Zentrum München)
  • Klassifikation von Spektren (2016)
  • Modellierung abhängiger/inhomogener Residuen in Regressionsmodellen für funktionale Responses
    (2015)
  • A Comparison of Different Akaike Information Criteria in Linear Mixed Models (2014)
  • Elucidating multivariate effects of various ECG parameters on mortality and evaluation of potentially
    underlying genetic components through genomewide association analyses (2014; Kooperation mit dem
    Helmholtz-Zentrum München)
  • Novelty Detection Methods in High-Dimensional Spaces With An Application On Spectral Data (2014;
    Kooperation mit Siemens)
  • Identifiability in Scalar-on-Functions Regression (2013)
  • Spatio-temporale Aspekte des Screening-Programms für Kolonkarzinome in Bayern (2011; mit Torsten
    Hothorn)

 

Diploma Theses

  • Statistischer Performance-Vergleich für Klima-Chemie-Modelle (2012; mit Torsten Hothorn)
  • Conditional Akaike Information Criteria in Generalized Linear Mixed Models (2011; mit Thomas Kneib)