Dr. Sven Klaaßen

Research Associate
Address
Office
Office hours
- by appointment
Contact
Research Interests
- Inference in High-Dimensional Settings
- Machine Learning
- Causal Inference
- Deep Learning
- Empirical Processes
Curriculum Vitae (available here)
Publications
Farbmacher, H., Guber, R. and Klaassen, S., 2020. Instrument Validity Tests with Causal Forests. Journal of Business & Economic Statistics, pp.1-10. (available here)
Klaassen, S., Kück, J. and Spindler, M., 2021. Transformation models in high-dimensions. Journal of Business & Economic Statistics, (just-accepted), pp.1-30. (available here)
Klaassen, S., 2020. Essays on Valid Inference in High-dimensions, Dissertation
Working Papers
Klaassen, S., Kück, J., Spindler, M. and Chernozhukov, V., 2018. Uniform inference in high-dimensional gaussian graphical models. (Revised & Resubmit at Biometrika, available here)
Bach, P., Klaassen, S., Kueck, J. and Spindler, M., 2020. Uniform Inference in High-Dimensional Generalized Additive Models. (available here)
Klaassen, S., 2021. A Note on High-Dimensional Confidence Regions. (available here)
Work in Progress
Quantile Boosting
Average Conditional Quantile Treatment Effects
Adaptive diskrete Smoothing (with Ye Luo and Martin Spindler)
Controlling the False Discovery Rate for Heterogenous Treatment Effects
Education
2022 | Visiting Scholar at MIT, Department of Economics |
Since 2021 | Postdoc in Statistics, Hamburg Business School (Hamburg University) |
2020 | Ph. D. in Statistics, Hamburg Business School (Hamburg University) |
2016 | M.Sc. Business Mathematics, University of Hamburg |
2014 | B.Sc. Business Mathematics, University of Hamburg |