compboost: Modular Framework for Component-Wise Boosting. - Daniel Schalk; Janek Thomas; Bernd Bischl (J. Open Source Softw., 2018)

compboost. - Daniel Schalk; Janek Thomas; Bernd Bischl (Zenodo, 2018)

Component-Wise Boosting of Targets for Multi-Output Prediction. - Quay Au; Daniel Schalk; Giuseppe Casalicchio; Ramona Schödel; Clemens Stachl; Bernd Bischl (CoRR, 2019)

Automatic Componentwise Boosting: An Interpretable AutoML System. - Stefan Coors; Daniel Schalk; Bernd Bischl; David Rügamer (CoRR, 2021)

Distributed non-disclosive validation of predictive models by a modified ROC-GLM. - Daniel Schalk; Verena S. Hoffmann; Bernd Bischl; Ulrich Mansmann (CoRR, 2022)

Multimodal Deep Learning. - Cem Akkus; Luyang Chu; Vladana Djakovic; Steffen Jauch-Walser; Philipp Koch; Giacomo Loss; Christopher Marquardt; Marco Moldovan; Nadja Sauter; Maximilian Schneider; Rickmer Schulte; Karol Urbanczyk; et al. (CoRR, 2023)

dsBinVal: Conducting distributed ROC analysis using DataSHIELD. - Daniel Schalk; Verena S. Hoffmann; Bernd Bischl; Ulrich Mansmann (J. Open Source Softw., 2023)

Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization. - Daniel Schalk; Bernd Bischl; David Rügamer (J. Comput. Graph. Stat., 2023)

Privacy-preserving and lossless distributed estimation of high-dimensional generalized additive mixed models. - Daniel Schalk; Bernd Bischl; David Rügamer (Stat. Comput., 2024)