Torsten Hothorn

ORCID

Publication Activity (10 Years)

Years Active: 2002-2023
Publications (10 Years): 16

Top Venues

Technical University of Dortmund, Germany (PHD)

Education History

Technical University of Dortmund, Germany

PHD

Publications

David Rügamer, Philipp F. M. Baumann, Thomas Kneib, Torsten Hothorn
Probabilistic time series forecasts with autoregressive transformation models. Stat. Comput. 33 (2) (2023)
Lucas Kook, Andrea Götschi, Philipp F. M. Baumann, Torsten Hothorn, Beate Sick
Deep interpretable ensembles. CoRR (2022)
Gabriele Campanella, Lucas Kook, Ida Häggström, Torsten Hothorn, Thomas J. Fuchs
Deep conditional transformation models for survival analysis. CoRR (2022)
Lucas Kook, Lisa Herzog, Torsten Hothorn, Oliver Dürr, Beate Sick
Deep and interpretable regression models for ordinal outcomes. Pattern Recognit. 122 (2022)
Lucas Kook, Torsten Hothorn
Regularized Transformation Models: The tramnet Package. R J. 13 (1) (2021)
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)
Torsten Hothorn, Achim Zeileis
Predictive Distribution Modeling Using Transformation Forests. J. Comput. Graph. Stat. 30 (4) (2021)
Bálint Tamási, Torsten Hothorn
tramME: Mixed-Effects Transformation Models Using Template Model Builder. R J. 13 (2) (2021)
Lucas Kook, Lisa Herzog, Torsten Hothorn, Oliver Dürr, Beate Sick
Ordinal Neural Network Transformation Models: Deep and interpretable regression models for ordinal outcomes. CoRR (2020)
Philipp F. M. Baumann, Torsten Hothorn, David Rügamer
Deep Conditional Transformation Models. CoRR (2020)
Beate Sick, Torsten Hothorn, Oliver Dürr
Deep transformation models: Tackling complex regression problems with neural network based transformation models. ICPR (2020)
Torsten Hothorn
Transformation boosting machines. Stat. Comput. 30 (1) (2020)
Beate Sick, Torsten Hothorn, Oliver Dürr
Deep transformation models: Tackling complex regression problems with neural network based transformation models. CoRR (2020)
Heidi Seibold, Torsten Hothorn, Achim Zeileis
Generalised linear model trees with global additive effects. Adv. Data Anal. Classif. 13 (3) (2019)
Benjamin Hofner, Thomas Kneib, Torsten Hothorn
A unified framework of constrained regression. Stat. Comput. 26 (1-2) (2016)
Torsten Hothorn, Achim Zeileis
Partykit: a modular toolkit for recursive partytioning in R. J. Mach. Learn. Res. 16 (2015)
Alexander Hapfelmeier, Torsten Hothorn, Kurt Ulm, Carolin Strobl
A new variable importance measure for random forests with missing data. Stat. Comput. 24 (1) (2014)
Benjamin Hofner, Torsten Hothorn, Thomas Kneib
Variable selection and model choice in structured survival models. Comput. Stat. 28 (3) (2013)
Alexander Hapfelmeier, Torsten Hothorn, Kurt Ulm
Recursive partitioning on incomplete data using surrogate decisions and multiple imputation. Comput. Stat. Data Anal. 56 (6) (2012)
Friedrich Leisch, Manuel J. A. Eugster, Torsten Hothorn
Executable Papers for the R Community: The R2 Platform for Reproducible Research. ICCS (2011)
Torsten Hothorn, Friedrich Leisch
Case studies in reproducibility. Briefings Bioinform. 12 (3) (2011)
Peter Bühlmann, Torsten Hothorn
Twin Boosting: improved feature selection and prediction. Stat. Comput. 20 (2) (2010)
Torsten Hothorn, Peter Bühlmann, Thomas Kneib, Matthias Schmid, Benjamin Hofner
Model-based Boosting 2.0. J. Mach. Learn. Res. 11 (2010)
Anne-Laure Boulesteix, Torsten Hothorn
Testing the additional predictive value of high-dimensional molecular data. BMC Bioinform. 11 (2010)
Matthias Schmid, Sergej Potapov, Annette B. Pfahlberg, Torsten Hothorn
Estimation and regularization techniques for regression models with multidimensional prediction functions. Stat. Comput. 20 (2) (2010)
Xuefei Mi, Tetsuhisa Miwa, Torsten Hothorn
New Numerical Algorithm for Multivariate Normal Probabilities in Package mvtnorm. R J. 1 (1) (2009)
Carolin Strobl, Torsten Hothorn, Achim Zeileis
Party on! R J. 1 (2) (2009)
Matthias Schmid, Torsten Hothorn
Boosting additive models using component-wise P-Splines. Comput. Stat. Data Anal. 53 (2) (2008)
Matthias Schmid, Torsten Hothorn
Flexible boosting of accelerated failure time models. BMC Bioinform. 9 (2008)
Gabriele Wolz, Anton Nömayr, Torsten Hothorn, Joachim Hornegger, Wolfgang Römer, Werner Bautz, Torsten Kuwert
Comparison of performance between rigid and non-rigid software registering CT to FDG-PET. Int. J. Comput. Assist. Radiol. Surg. 2 (3-4) (2007)
Carolin Strobl, Anne-Laure Boulesteix, Achim Zeileis, Torsten Hothorn
Bias in random forest variable importance measures: Illustrations, sources and a solution. BMC Bioinform. 8 (2007)
Torsten Hothorn, Peter Bühlmann
Model-based boosting in high dimensions. Bioinform. 22 (22) (2006)
A. Peters, Torsten Hothorn, Berthold Lausen
Generalised indirect classifiers. Comput. Stat. Data Anal. 49 (3) (2005)
Radim Chrástek, Matthias Wolf, Klaus Donath, Heinrich Niemann, Dietrich Paulus, Torsten Hothorn, Berthold Lausen, Robert Lämmer, Christian Y. Mardin, Georg Michelson
Automated segmentation of the optic nerve head for diagnosis of glaucoma. Medical Image Anal. 9 (4) (2005)
Torsten Hothorn, Berthold Lausen
Bundling classifiers by bagging trees. Comput. Stat. Data Anal. 49 (4) (2005)
David Meyer, Friedrich Leisch, Torsten Hothorn, Kurt Hornik
: An XML Format for Statistical Data. Comput. Stat. 19 (3) (2004)
Torsten Hothorn, Berthold Lausen
Bagging tree classifiers for laser scanning images: a data- and simulation-based strategy. Artif. Intell. Medicine 27 (1) (2003)
Radim Chrástek, Matthias Wolf, Klaus Donath, Heinrich Niemann, Torsten Hothorn, Berthold Lausen, Robert Lämmer, Christian Y. Mardin, Georg Michelson
Automated Segmentation of the Optic Nerve Head for Glaucoma Diagnosis. Bildverarbeitung für die Medizin (2003)
Torsten Hothorn, Berthold Lausen
Double-bagging: combining classifiers by bootstrap aggregation. Pattern Recognit. 36 (6) (2003)
Torsten Hothorn, Berthold Lausen
On the exact distribution of maximally selected rank statistics. Comput. Stat. Data Anal. 43 (2) (2003)
Torsten Hothorn, Kurt Hornik
Exact Nonparametric Inference in R. COMPSTAT (2002)
David Meyer, Friedrich Leisch, Torsten Hothorn, Kurt Hornik
StatDataML: An XML Format for Statistical Data. COMPSTAT (2002)
Torsten Hothorn, Berthold Lausen
Bagging Tree Classifiers for Glaucoma Diagnosis. COMPSTAT (2002)

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Publication Activity (10 Years)

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Torsten Hothorn