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

Collection of old exams from the SLDS chair.  

Self-enrollment key: have_fun_with_exams!

This Moodle course contains Master's thesis topics from the SLDS research group on Automated Machine Learning and Optimization.

Self enrollment key: thesis

Internes Wiki der AG Augustin 

Recap Material for Master Statistics and Data Science

Reading group organisiert für alle Institutsangehörige von Studierenden

password: ReadingGroup

Interne Organisation am Institut.

Organization of the doctoral program of the Statistics department.

Please contact Michael Windmann for enrollment details.

Alle Informationen rund um die CIP-Pools des Instituts für Statistik.

  • Über Ankündigungen werden alle aktuellen Ankündigungen, welche die CIP-Pools betreffen, kommuniziert.
  • Im Wiki finden sich alle nützlichen Informationen rund um die CIP-Pools.

Das Passwort für die Einschreibung lautet: "cip-pool-stat"

Internal communication at the department of Statistics

Enrollment key: "insti2020tut"