Research

Publications (Peer-reviewed)

Philipp Bach, Oliver Schacht, Victor Chernozhukov, Sven Klaassen, Martin Spindler (2024), Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Study, Conference on Causal Learning and Reasoning, Proceedings of Machine Learning Research, 236, 1065-1117, available online.
Philipp Bach, Victor Chernozhukov, Martin Spindler (2024). Heterogeneity in the U.S. Gender Wage Gap. Journal of the Royal Statistical Society: Series A, 187(1), 209-230, available online.
Philipp Bach, Victor Chernozhukov, Malte S. Kurz, , Martin Spindler, Sven Klaassen (2024). DoubleML - An Object-Oriented Implementation of Double Machine Learning in R. DoubleML: An Object-Oriented Implementation of Double Machine Learning in R. Journal of Statistical Software, 108(3), 1–56, available online.
Philipp Bach, Victor Chernozhukov, Malte S. Kurz, , Martin Spindler (2022). DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python. Journal of Machine Learning Research 23 (53), 1–6, available online.
Philipp Bach, Helmut Farbmacher, Martin Spindler, Semiparametric count data modeling with an application to health service demand, Econometrics and Statistics, 8, 125-140, 2018, , available online.

Sven Klaassen, Jan Teichert-Kluge, Philipp Bach, Victor Chernozhukov, Martin Spindler, Suhas Vijaykumar, DoubleMLDeep: Estimation of Causal Effects with Multimodal Data, 2024, available at arxiv.
Philipp Bach, Sven Klaassen, Jannis Kueck, Martin Spindler, Estimation and Uniform Inference in Sparse High-Dimensional Additive Models, Working Paper, available at arxiv, 2020.
Philipp Bach, Victor Chernozhukov, Martin Spindler, Insights from Optimal Pandemic Shielding in a Multi-Group SEIR Framework, Working Paper, available at arxiv, 2020.
Philipp Bach, Victor Chernozhukov, Martin Spindler, Closing the U.S. gender wage gap requires understanding its heterogeneity, Working Paper, available at arxiv, 2018.
Philipp Bach, Victor Chernozhukov, Martin Spindler, Valid Simultaneous Inference in High-Dimensional Settings (with the HDM package for R), Working Paper, available at arXiv, 2018.

A list of talks and presentations is available here.