Gunnar König
About
Since May 2019 I am a PhD student at LMU, supervised by Prof. Moritz Grosse-Wentrup (Universität Wien) and Prof. Bernd Bischl. I am interested in causality and interpretable machine learning with applications in precision medicine.
I obtained my Bachelor's Degree (B.Sc.) in Information Systems at TU Munich and my Master's Degree (M.Sc.) in Data Science at LMU.
Contact
Institut für Statistik
Ludwig-Maximilians-Universität München
Ludwigstraße 33
D-80539 München
Room 139
gunnar.koenig [at] stat.uni-muenchen.de
Research Interests
- Interpretable Machine learning
- Causal Inference
You Can Find me on
References
- König G, Freiesleben T, Grosse-Wentrup M (2023) Improvement-focused Causal Recourse (ICR) 37th AAAI Conference,
- Luther C, König G, Grosse-Wentrup M (2023) Efficient SAGE Estimation via Causal Structure Learning AISTATS,
- Molnar C, König G, Herbinger J, Freiesleben T, Dandl S, Scholbeck CA, Casalicchio G, Grosse-Wentrup M, Bischl B (2022) General pitfalls of model-agnostic interpretation methods for machine learning models International Workshop on Extending Explainable AI Beyond Deep Models and Classifiers, pp. 39–68. Springer.
- Freiesleben T, König G, Molnar C, Tejero-Cantero A (2022) Scientific inference with interpretable machine learning: Analyzing models to learn about real-world phenomena. arXiv preprint arXiv:2206.05487.
- König G, Freiesleben T, Grosse-Wentrup M (2021) A causal perspective on meaningful and robust algorithmic recourse. arXiv preprint arXiv:2107.07853.
- König G, Freiesleben T, Bischl B, Casalicchio G, Grosse-Wentrup M (2021) Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT). arXiv preprint arXiv:2106.08086.
- König G, Molnar C, Bischl B, Grosse-Wentrup M (2020) Relative Feature Importance. ICPR.
link. - Molnar C, König G, Bischl B, Casalicchio G (2020) Model-agnostic Feature Importance and Effects with Dependent Features–A Conditional Subgroup Approach. arXiv preprint arXiv:2006.04628.
- König G, Grosse-Wentrup M (2019) A Causal Perspective on Challenges for AI in Precision Medicine.
link.