Deep Conditional Transformation Models. - Philipp F. M. Baumann; Torsten Hothorn; David Rügamer (ECML/PKDD (3), 2021)

Translational Equivariance in Kernelizable Attention. - Max Horn; Kumar Shridhar; Elrich Groenewald; Philipp F. M. Baumann (CoRR, 2021)

Transforming Autoregression: Interpretable and Expressive Time Series Forecast. - David Rügamer; Philipp F. M. Baumann; Thomas Kneib; Torsten Hothorn (CoRR, 2021)

Deep interpretable ensembles. - Lucas Kook; Andrea Götschi; Philipp F. M. Baumann; Torsten Hothorn; Beate Sick (CoRR, 2022)

Selective inference for additive and linear mixed models. - David Rügamer; Philipp F. M. Baumann; Sonja Greven (Comput. Stat. Data Anal., 2022)

What drives inflation and how? Evidence from additive mixed models selected by cAIC. - Philipp F. M. Baumann; Enzo Rossi; Alexander Volkmann (Frontiers Appl. Math. Stat., 2023)

deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression. - David Rügamer; Chris Kolb; Cornelius Fritz; Florian Pfisterer; Philipp Kopper; Bernd Bischl; Ruolin Shen; Christina Bukas; Lisa Barros de Andrade e Sousa; Dominik Thalmeier; Philipp F. M. Baumann; Lucas Kook; et al. (J. Stat. Softw., 2023)

Over-optimism in unsupervised microbiome analysis: Insights from network learning and clustering. - Theresa Ullmann; Stefanie Peschel; Philipp F. M. Baumann; Christian L. Müller; Anne-Laure Boulesteix (PLoS Comput. Biol., 2023)

Probabilistic time series forecasts with autoregressive transformation models. - David Rügamer; Philipp F. M. Baumann; Thomas Kneib; Torsten Hothorn (Stat. Comput., 2023)

How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression. - Lucas Kook; Chris Kolb; Philipp Schiele; Daniel Dold; Marcel Arpogaus; Cornelius Fritz; Philipp F. M. Baumann; Philipp Kopper; Tobias Pielok; Emilio Dorigatti; David Rügamer (UAI, 2024)

Estimating Conditional Distributions with Neural Networks Using R Package deeptrafo. - Lucas Kook; Philipp F. M. Baumann; Oliver Dürr; Beate Sick; David Rügamer (J. Stat. Softw., 2024)