Christoph Molnar

About

Since october 2017 I am a PhD student at the working group for Computational Statistics at the Ludwig-Maximilians-University Munich, doing my research on Interpretable Machine Learning.

I obtained a Bachelor's Degree (B.Sc.) and Master's Degree (M.Sc.) in Statistics from the Ludwig-Maximilians-University Munich.

Contact

Institut für Statistik

Ludwig-Maximilians-Universität München

Ludwigstraße 33

D-80539 München

Room 139

Phone: +49 89 2180 2763

christoph.molnar [at] stat.uni-muenchen.de

Research Interests

You Can Find me on

References

  1. Molnar C (2019) Interpretable Machine Learning.
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  2. Molnar C, Casalicchio G, Bischl B (2019) Quantifying Interpretability of Arbitrary Machine Learning Models Through Functional Decomposition. arXiv preprint arXiv:1904.03867. arXiv:1904.03867.
  3. Scholbeck CA, Molnar C, Heumann C, Bischl B, Casalicchio G (2019) Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model Agnostic Interpretations. arXiv preprint arXiv:1904.03959. arXiv:1904.03959.
  4. Molnar C, Casalicchio G, Bischl B (2018) iml: An R package for Interpretable Machine Learning. The Journal of Open Source Software 3, 786. 10.21105/joss.00786.
  5. Casalicchio G, Molnar C, Bischl B (2018) Visualizing the Feature Importance for Black Box Models. arXiv preprint arXiv:1804.06620. arXiv:1804.06620.