| Deep Conditional Transformation Models PFM Baumann, T Hothorn, D Rügamer European Conference on Machine Learning and Principles and Practice of …, 2021 | 20 | 2021 |
| Estimating the Effect of Central Bank Independence on Inflation Using Longitudinal Targeted Maximum Likelihood Estimation PFM Baumann, M Schomaker, E Rossi Journal of Causal Inference 9 (1), 109--146, 2021 | 17 | 2021 |
| What drives inflation and how? Evidence from additive mixed models selected by cAIC PFM Baumann, E Rossi, A Volkmann SNB Working Paper Series, 2021 | 14 | 2021 |
| Selective inference for additive and linear mixed models D Rügamer, PFM Baumann, S Greven Computational Statistics & Data Analysis 167, 107350, 2022 | 11 | 2022 |
| deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression D Rügamer, C Kolb, C Fritz, F Pfisterer, B Bischl, R Shen, C Bukas, ... Journal of Statistical Software (provisionally accepted), 2022 | 9 | 2022 |
| Deep interpretable ensembles L Kook, A Götschi, PFM Baumann, T Hothorn, B Sick arXiv preprint arXiv:2205.12729, 2022 | 8 | 2022 |
| Probabilistic time series forecasts with autoregressive transformation models D Rügamer, PFM Baumann, T Kneib, T Hothorn Statistics and Computing 33 (2), 37, 2023 | 7 | 2023 |
| Translational Equivariance in Kernelizable Attention M Horn, K Shridhar, E Groenewald, PFM Baumann arXiv preprint arXiv:2102.07680, 2021 | 5 | 2021 |
| Estimating Conditional Distributions with Neural Networks using R package deeptrafo L Kook, PFM Baumann, O Dürr, B Sick, D Rügamer arXiv preprint arXiv:2211.13665, 2022 | 4 | 2022 |
| Doubly Robust Estimation of Average Treatment Effects on the Treated through Marginal Structural Models M Schomaker, PFM Baumann Observational Studies 9 (3), 43-57, 2023 | | 2023 |
