Allgemeine Kurse

This Moodle page contains thesis topics supervised by Giuseppe Casalicchio who works at the SLDS chair and conducts research on Interpretable Machine Learning and Empirical Machine Learning. 

The thesis topics mainly focus on:

• Interpretable ML: Enhancing transparency and interpretability in ML for tabular data.
• Empirical ML: Addressing research questions through empirical studies, including conducting (large-scale) benchmark experiments and analyzing the results.

Self enrollment key: ml_thesis

Recap Material for Master Statistics and Data Science

Reading group organisiert für alle Institutsangehörige von Studierenden

password: ReadingGroup

Organization of the doctoral program of the Statistics department.

Please contact Michael Windmann for enrollment details.