Philipp F. M. Baumann

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 11

Top Topics

Nonrigid Registration

Merging Algorithm

Autoregressive Moving Average

Top Venues

J. Stat. Softw.

Comput. Stat. Data Anal.

Publications

Lucas Kook, Chris Kolb, Philipp Schiele, Daniel Dold, Marcel Arpogaus, Cornelius Fritz, Philipp F. M. Baumann, Philipp Kopper, Tobias Pielok, Emilio Dorigatti, David Rügamer
How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression. CoRR (2024)
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
deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression. J. Stat. Softw. 105 (2) (2023)
David Rügamer, Philipp F. M. Baumann, Thomas Kneib, Torsten Hothorn
Probabilistic time series forecasts with autoregressive transformation models. Stat. Comput. 33 (2) (2023)
Theresa Ullmann, Stefanie Peschel, Philipp F. M. Baumann, Christian L. Müller, Anne-Laure Boulesteix
Over-optimism in unsupervised microbiome analysis: Insights from network learning and clustering. PLoS Comput. Biol. 19 (1) (2023)
Philipp F. M. Baumann, Enzo Rossi, Alexander Volkmann
What drives inflation and how? Evidence from additive mixed models selected by cAIC. Frontiers Appl. Math. Stat. 9 (2023)
Lucas Kook, Andrea Götschi, Philipp F. M. Baumann, Torsten Hothorn, Beate Sick
Deep interpretable ensembles. CoRR (2022)
David Rügamer, Philipp F. M. Baumann, Sonja Greven
Selective inference for additive and linear mixed models. Comput. Stat. Data Anal. 167 (2022)
David Rügamer, Philipp F. M. Baumann, Thomas Kneib, Torsten Hothorn
Transforming Autoregression: Interpretable and Expressive Time Series Forecast. CoRR (2021)
Philipp F. M. Baumann, Torsten Hothorn, David Rügamer
Deep Conditional Transformation Models. ECML/PKDD (3) (2021)
Max Horn, Kumar Shridhar, Elrich Groenewald, Philipp F. M. Baumann
Translational Equivariance in Kernelizable Attention. CoRR (2021)
Philipp F. M. Baumann, Torsten Hothorn, David Rügamer
Deep Conditional Transformation Models. CoRR (2020)