Object circles: modeling physical objects as social relationships. - Florian Michahelles; Philipp Probst (MUM, 2012)

mlr Tutorial. - Julia Schiffner; Bernd Bischl; Michel Lang; Jakob Richter; Zachary M. Jones; Philipp Probst; Florian Pfisterer; Mason Gallo; Dominik Kirchhoff; Tobias Kühn; Janek Thomas; Lars Kotthoff (CoRR, 2016)

To Tune or Not to Tune the Number of Trees in Random Forest. - Philipp Probst; Anne-Laure Boulesteix (J. Mach. Learn. Res., 2017)

Multilabel Classification with R Package mlr. - Philipp Probst; Quay Au; Giuseppe Casalicchio; Clemens Stachl; Bernd Bischl (R J., 2017)

Random forest versus logistic regression: a large-scale benchmark experiment. - Raphaël Couronné; Philipp Probst; Anne-Laure Boulesteix (BMC Bioinform., 2018)

Automatic Exploration of Machine Learning Experiments on OpenML. - Daniel Kühn; Philipp Probst; Janek Thomas; Bernd Bischl (CoRR, 2018)

Tunability: Importance of Hyperparameters of Machine Learning Algorithms. - Philipp Probst; Anne-Laure Boulesteix; Bernd Bischl (J. Mach. Learn. Res., 2019)

Hyperparameters and tuning strategies for random forest. - Philipp Probst; Marvin N. Wright; Anne-Laure Boulesteix (WIREs Data Mining Knowl. Discov., 2019)

Hyperparameters, tuning and meta-learning for random forest and other machine learning algorithms. - Philipp Probst (2019)

Learning multiple defaults for machine learning algorithms. - Florian Pfisterer; Jan N. van Rijn; Philipp Probst; Andreas C. Müller 002; Bernd Bischl (GECCO Companion, 2021)

Large-scale benchmark study of survival prediction methods using multi-omics data. - Moritz Herrmann; Philipp Probst; Roman Hornung; Vindi Jurinovic; Anne-Laure Boulesteix (Briefings Bioinform., 2021)