Teaching
SS24: Seminar Explainable Machine Learning [course]
WS22: Multivariate Statistics
SS22: Advanced Machine Learning [course]
SS22: Seminar Introduction to Causal Inference [course]
WS21: Seminar Philosophy and Explainable AI, jointly at MCMP and Statistics Departement, [course]
SS21: Seminar Causality and Graphical Models, LMU Munich, [course]
SS21: Current Research in Data Science, LMU Munich
WS20: Seminar Ethics in AI, LMU Munich, [course]
WS20: Seminar: Current Research and Applications in Interpretable Machine Learning, LMU Munich, [course]
SS20: Seminar Causality and Graphical Models, LMU Munich, [course]
SS19: Seminar Limitations of Interpretable Machine learning, LMU Munich, [course]
Supervision
Valentyn Melnychuck, Master thesis, Conditional Normalizing Flows for Interpretability, now PhD student with Prof. Feuerriegel (LMU) [website]
Christoph Luther, Master thesis, Causal Structure Learning for Shapley Value based interpretability, now PhD student with Prof. Moritz Grosse-Wentrup (Vienna)