Dr. David Rügamer

Dr. David Rügamer

I'm currently interim professor for Data Science at the LMU Munich. My research is at the intersection of statistics, machine and deep learning.

Publications

I try to keep publications up to date on my Google Scholar profile.

Software (R-packages)

  • deepregression Semi-Strutured Deep Distrobutional Regression on Github and soon CRAN.
  • selfmade SELective inference For Mixed and ADditive model Estimators on CRAN and Github
  • FDboost Boosting Functional Regression Models on CRAN and Github
  • cAIC4 Conditional Akaike Information Criterion for ‘lme4’ on CRAN and Github
  • iboost Inference for Model-based Boosting on Github
  • coinflibs Conditional Inference after Likelihood-based Selection on Github
  • effortless efficient operations on row-wise tensor product linked evaluations with special structures on Github

Talks, Workshops and Research Stays

  • 18. March ‘21 (Leuven, BE) Sampling-based Approaches for Valid Post-Selection Inference Seminar Series in Statistics, KU Leuven
  • 28. October ‘20 (Dortmund, GER) Semi-Structured Deep Distributional Regression. Regression approaches for large-scale high-dimensional data, Dortmund Data Science Centers
  • 15. October ‘20 (Bonn, GER) Semi-Structured Deep Distributional Regression. (Virtual) Institutskolloquium IMBIE
  • 29. July ‘20 (Munich, GER) Semi-Structured Deep Distributional Regression. Virtual Workshop by the Munich Center of Machine Learning
  • 26. February ‘20 (Munich, GER) Semi-Structured Deep Distributional Learning. Institutskolloquium, Department of Statistics, LMU Munich
  • January ‘20 (Xiamen, CHN) Short research stay and exchange with several people involved in the DFG RTG group High Dimensional Nonstationary Time Series
  • 21. March ‘19 (Munich, GER) Inference for L2-Boosting, DAGSTAT 2019, Machine Learning Session
  • 15. June ‘18 (Munich, GER) Estimation, Model Choice and Subsequent Inference: Methods for Additive and Functional Regression Models. Doctoral Dissertation Defense
  • 26. - 28. March 2018 (Frankfurt a.M., GER) Boosting Factor-Specific Functional Historical Models. Award Session, 64th Biometric Colloquium
  • 16. - 18. December 2017 (London, UK) Selective Inference for L2-Boosting. 10th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2017)
  • 23. - 25. July 2017 (Reisensburg, GER) Boosting functional regression models with FDboost. Statistical Computing 2017
  • 9. - 11. December 2016 (Seville, ESP) Boosting Factor-Specific Functional Historical Models. 9th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2016)
  • 30. November 2016 (Munich, GER) Selective Inference for L2-Boosting. Institutskolloquium, Department of Statistics LMU, Munich