Philipp F. M. Baumann

14 papers A 1Journal 12Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Deep interpretable ensembles. Neurocomputing Lucas Kook, Andrea Götschi, Philipp F. M. Baumann, Torsten Hothorn, Beate Sick
2024	J	`jnl`	Estimating Conditional Distributions with Neural Networks Using J. Stat. Softw. Lucas Kook, Philipp F. M. Baumann, Oliver Dürr, Beate Sick, David Rügamer
2024	A	`conf`	How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression. UAI Lucas Kook, Chris Kolb, Philipp Schiele, Daniel Dold, Marcel Arpogaus, Cornelius Fritz, Philipp F. M. Baumann, Philipp Kopper, Tobias Pielok, Emilio Dorigatti, David Rügamer
2024	J	`jnl`	How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression. CoRR Lucas Kook, Chris Kolb, Philipp Schiele, Daniel Dold, Marcel Arpogaus, Cornelius Fritz, Philipp F. M. Baumann, Philipp Kopper, Tobias Pielok, Emilio Dorigatti, David Rügamer
2023	J	`jnl`	Over-optimism in unsupervised microbiome analysis: Insights from network learning and clustering. PLoS Comput. Biol. Theresa Ullmann, Stefanie Peschel, Philipp F. M. Baumann, Christian L. Müller, Anne-Laure Boulesteix
2023	J	`jnl`	Probabilistic time series forecasts with autoregressive transformation models. Stat. Comput. David Rügamer, Philipp F. M. Baumann, Thomas Kneib, Torsten Hothorn
2023	J	`jnl`	What drives inflation and how? Evidence from additive mixed models selected by cAIC. Frontiers Appl. Math. Stat. Philipp F. M. Baumann, Enzo Rossi, Alexander Volkmann
2023	J	`jnl`	deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression. J. Stat. Softw. 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, Nadja Klein, Christian L. Müller
2022	J	`jnl`	Deep interpretable ensembles. CoRR Lucas Kook, Andrea Götschi, Philipp F. M. Baumann, Torsten Hothorn, Beate Sick
2022	J	`jnl`	Selective inference for additive and linear mixed models. Comput. Stat. Data Anal. David Rügamer, Philipp F. M. Baumann, Sonja Greven
2021	—	`conf`	Deep Conditional Transformation Models. ECML/PKDD (3) Philipp F. M. Baumann, Torsten Hothorn, David Rügamer
2021	J	`jnl`	Transforming Autoregression: Interpretable and Expressive Time Series Forecast. CoRR David Rügamer, Philipp F. M. Baumann, Thomas Kneib, Torsten Hothorn
2021	J	`jnl`	Translational Equivariance in Kernelizable Attention. CoRR Max Horn, Kumar Shridhar, Elrich Groenewald, Philipp F. M. Baumann
2020	J	`jnl`	Deep Conditional Transformation Models. CoRR Philipp F. M. Baumann, Torsten Hothorn, David Rügamer