Dr. Paul Wiemann
I am a postdoctoral research associate (German: Akademischer Rat a.Z.) at the chair of Statistics at the University of Göttingen, Germany. I hold degrees in Computer Science and Applied Statistics and received my PhD under the supervision of Prof. Dr. Thomas Kneib. Among other projects, I’m working as one of the main developers on the DFG funded software project Liesel (project number 443179956).
Publications & selected working papers
- Wiemann, P., Klein, N. & Kneib, T. (2022). Correcting for sample selection bias in Bayesian distributional regression models. Computational Statistics and Data Analysis, 168, 107382.
- Wiemann, P., Kneib, T. & Wagner, H. (2021). Effect Selection and regularization in structured additive distributional regression. In: Tadesse, M. and Vannucci, M. (eds.): Handbook of Bayesian Variable Selection. Chapman & Hall / CRC.
- Wiemann, P., Klein, N. & Kneib, T. (2021). Adaptive shrinkage of smooth functional effects towards a predefined functional subspace. arXiv:2101.05630.
- Wiemann, P., Kneib, T. & Hambuckers, J. (2021). Using the Softplus function to construct alternative link functions in generalized linear models and beyond arXiv:2111.14207.
- Bögel, P., Oltra, C., Sala, R., Lores, M., Upham, P., Dütschke, E., Schneider, U. & Wiemann, P. (2018). The role of attitudes in technology acceptance management: reflections on the case of hydrogen fuel cells in Europe. Journal of Cleaner Production, 188, 125–135.
- Wiemann, P., Wenger, S. & Magnor, M. (2011). CUDA expression templates. WSCG Communication Papers Proceedings, 185–192.
- Marques, I., Wiemann, P. & Kneib, T. (2022). A spatial multi-resolution model for forestry datasets. Working paper, first authorship is shared between Marques and Wiemann
- Liesel: A Python framework for Bayesian models and custom inference algorithm. https://www.github.com/liesel-devs/liesel
- Alfred3: Treffenstädt, C., Brachem, J., & Wiemann, P. (2021). Alfred3 - A library for rapid experiment development. https://doi.org/10.5281/zenodo.1437219
- Bayesian Statistics
- Computational Statistics
- Variational Approximation
- Shrinkage Priors
- Spatial Statistics
I’ve taught Bachelor and Master students at the University of Göttingen and held a tutorial in a summer school. During my time at the TU Dortmund University - as a Step-in Professor in the winter term 2021 - I was responsible for an introductory statistics class for computer science students and also for the class Introductory Case Studies from the data science master program. I have guided and assessed several theses (Bachelor and Master). Please see https://www.uni-goettingen.de/en/470953.html for a list of topics the chair currently offers.
A selected list of courses I’ve taught:
- Linear Models @ University of Göttingen
- Advanced Regression Models @ University of Göttingen
- Introduction to R @ University of Göttingen
- Probability and mathematical statistics @ TU Dortmund University
- Recent topics of Bayesian statistics @ University of Göttingen
- Computational methods in Bayesian statistics @ University of Göttingen
- Introductory Case Studies @ TU Dortmund University
- Spatial Statistics @ University of Göttingen