Exact Nonparametric Inference in R. - Torsten Hothorn; Kurt Hornik (COMPSTAT, 2002)

Bagging Tree Classifiers for Glaucoma Diagnosis. - Torsten Hothorn; Berthold Lausen (COMPSTAT, 2002)

StatDataML: An XML Format for Statistical Data. - David Meyer; Friedrich Leisch; Torsten Hothorn; Kurt Hornik (COMPSTAT, 2002)

Automated Segmentation of the Optic Nerve Head for Glaucoma Diagnosis. - Radim Chrástek; Matthias Wolf 001; Klaus Donath; Heinrich Niemann; Torsten Hothorn; Berthold Lausen; Robert Lämmer; Christian Y. Mardin; Georg Michelson (Bildverarbeitung für die Medizin, 2003)

Bagging tree classifiers for laser scanning images: a data- and simulation-based strategy. - Torsten Hothorn; Berthold Lausen (Artif. Intell. Medicine, 2003)

On the exact distribution of maximally selected rank statistics. - Torsten Hothorn; Berthold Lausen (Comput. Stat. Data Anal., 2003)

Double-bagging: combining classifiers by bootstrap aggregation. - Torsten Hothorn; Berthold Lausen (Pattern Recognit., 2003)

Bundling classifiers with an application to glaucoma diagnosis. - Torsten Hothorn (2003)

StatDataML: An XML Format for Statistical Data. - David Meyer; Friedrich Leisch; Torsten Hothorn; Kurt Hornik (Comput. Stat., 2004)

Bundling classifiers by bagging trees. - Torsten Hothorn; Berthold Lausen (Comput. Stat. Data Anal., 2005)

Generalised indirect classifiers. - A. Peters; Torsten Hothorn; Berthold Lausen (Comput. Stat. Data Anal., 2005)

Automated segmentation of the optic nerve head for diagnosis of glaucoma. - Radim Chrástek; Matthias Wolf 001; Klaus Donath; Heinrich Niemann; Dietrich Paulus; Torsten Hothorn; Berthold Lausen; Robert Lämmer; Christian Y. Mardin; Georg Michelson (Medical Image Anal., 2005)

Model-based boosting in high dimensions. - Torsten Hothorn; Peter Bühlmann (Bioinform., 2006)

Bias in random forest variable importance measures: Illustrations, sources and a solution. - Carolin Strobl; Anne-Laure Boulesteix; Achim Zeileis; Torsten Hothorn (BMC Bioinform., 2007)

Comparison of performance between rigid and non-rigid software registering CT to FDG-PET. - Gabriele Wolz; Anton Nömayr; Torsten Hothorn; Joachim Hornegger; Wolfgang Römer; Werner Bautz; Torsten Kuwert (Int. J. Comput. Assist. Radiol. Surg., 2007)

Flexible boosting of accelerated failure time models. - Matthias Schmid; Torsten Hothorn (BMC Bioinform., 2008)

Boosting additive models using component-wise P-Splines. - Matthias Schmid; Torsten Hothorn (Comput. Stat. Data Anal., 2008)

New Numerical Algorithm for Multivariate Normal Probabilities in Package mvtnorm. - Xuefei Mi; Tetsuhisa Miwa; Torsten Hothorn (R J., 2009)

Party on! - Carolin Strobl; Torsten Hothorn; Achim Zeileis (R J., 2009)

Testing the additional predictive value of high-dimensional molecular data. - Anne-Laure Boulesteix; Torsten Hothorn (BMC Bioinform., 2010)

Model-based Boosting 2.0. - Torsten Hothorn; Peter Bühlmann; Thomas Kneib; Matthias Schmid; Benjamin Hofner (J. Mach. Learn. Res., 2010)

Twin Boosting: improved feature selection and prediction. - Peter Bühlmann; Torsten Hothorn (Stat. Comput., 2010)

Estimation and regularization techniques for regression models with multidimensional prediction functions. - Matthias Schmid; Sergej Potapov; Annette B. Pfahlberg; Torsten Hothorn (Stat. Comput., 2010)

Case studies in reproducibility. - Torsten Hothorn; Friedrich Leisch (Briefings Bioinform., 2011)

Executable Papers for the R Community: The R2 Platform for Reproducible Research. - Friedrich Leisch; Manuel J. A. Eugster; Torsten Hothorn (ICCS, 2011)

Recursive partitioning on incomplete data using surrogate decisions and multiple imputation. - Alexander Hapfelmeier; Torsten Hothorn; Kurt Ulm (Comput. Stat. Data Anal., 2012)

Variable selection and model choice in structured survival models. - Benjamin Hofner; Torsten Hothorn; Thomas Kneib (Comput. Stat., 2013)

A new variable importance measure for random forests with missing data. - Alexander Hapfelmeier; Torsten Hothorn; Kurt Ulm; Carolin Strobl (Stat. Comput., 2014)

Partykit: a modular toolkit for recursive partytioning in R. - Torsten Hothorn; Achim Zeileis (J. Mach. Learn. Res., 2015)

A unified framework of constrained regression. - Benjamin Hofner; Thomas Kneib; Torsten Hothorn (Stat. Comput., 2016)

Generalised linear model trees with global additive effects. - Heidi Seibold; Torsten Hothorn; Achim Zeileis (Adv. Data Anal. Classif., 2019)

Deep transformation models: Tackling complex regression problems with neural network based transformation models. - Beate Sick; Torsten Hothorn; Oliver Dürr (ICPR, 2020)

Ordinal Neural Network Transformation Models: Deep and interpretable regression models for ordinal outcomes. - Lucas Kook; Lisa Herzog; Torsten Hothorn; Oliver Dürr; Beate Sick (CoRR, 2020)

Transformation boosting machines. - Torsten Hothorn (Stat. Comput., 2020)

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

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

Predictive Distribution Modeling Using Transformation Forests. - Torsten Hothorn; Achim Zeileis (J. Comput. Graph. Stat., 2021)

Regularized Transformation Models: The tramnet Package. - Lucas Kook; Torsten Hothorn (R J., 2021)

tramME: Mixed-Effects Transformation Models Using Template Model Builder. - Bálint Tamási; Torsten Hothorn (R J., 2021)

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

Deep conditional transformation models for survival analysis. - Gabriele Campanella; Lucas Kook; Ida Häggström; Torsten Hothorn; Thomas J. Fuchs (CoRR, 2022)

Deep and interpretable regression models for ordinal outcomes. - Lucas Kook; Lisa Herzog; Torsten Hothorn; Oliver Dürr; Beate Sick (Pattern Recognit., 2022)

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

Remembering Friedrich "Fritz" Leisch. - Bettina Grün; Kurt Hornik; Torsten Hothorn; Theresa Scharl; Achim Zeileis (R J., 2025)

Gradient boosting for generalised additive mixed models. - Lars Knieper; Torsten Hothorn; Elisabeth Bergherr; Colin Griesbach (Stat. Comput., 2025)