Model-Agnostic Approaches to Multi-Objective Simultaneous Hyperparameter Tuning and Feature Selection. - Martin Binder; Julia Moosbauer; Janek Thomas; Bernd Bischl (CoRR, 2019)

mlr3: A modern object-oriented machine learning framework in R. - Michel Lang; Martin Binder; Jakob Richter; Patrick Schratz; Florian Pfisterer; Stefan Coors; Quay Au; Giuseppe Casalicchio; Lars Kotthoff; Bernd Bischl (J. Open Source Softw., 2019)

mlr3: A modern object-oriented machine learning framework in R. - Michel Lang; Martin Binder; Jakob Richter; Patrick Schratz; Florian Pfisterer; Stefan Coors; Quay Au; Giuseppe Casalicchio; Lars Kotthoff; Bernd Bischl (Zenodo, 2019)

Multi-objective hyperparameter tuning and feature selection using filter ensembles. - Martin Binder; Julia Moosbauer; Janek Thomas; Bernd Bischl (GECCO, 2020)

Multi-Objective Counterfactual Explanations. - Susanne Dandl; Christoph Molnar; Martin Binder; Bernd Bischl (PPSN (1), 2020)

Mutation is all you need. - Lennart Schneider; Florian Pfisterer; Martin Binder; Bernd Bischl (CoRR, 2021)

YAHPO Gym - Design Criteria and a new Multifidelity Benchmark for Hyperparameter Optimization. - Florian Pfisterer; Lennart Schneider; Julia Moosbauer; Martin Binder; Bernd Bischl (CoRR, 2021)

mlr3pipelines - Flexible Machine Learning Pipelines in R. - Martin Binder; Florian Pfisterer; Michel Lang; Lennart Schneider; Lars Kotthoff; Bernd Bischl (J. Mach. Learn. Res., 2021)

YAHPO Gym - An Efficient Multi-Objective Multi-Fidelity Benchmark for Hyperparameter Optimization. - Florian Pfisterer; Lennart Schneider; Julia Moosbauer; Martin Binder; Bernd Bischl (AutoML, 2022)

Multi-Objective Hyperparameter Optimization - An Overview. - Florian Karl; Tobias Pielok; Julia Moosbauer; Florian Pfisterer; Stefan Coors; Martin Binder; Lennart Schneider; Janek Thomas; Jakob Richter; Michel Lang; Eduardo C. Garrido-Merchán; Jürgen Branke; et al. (CoRR, 2022)

Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers. - Julia Moosbauer; Martin Binder; Lennart Schneider; Florian Pfisterer; Marc Becker; Michel Lang; Lars Kotthoff; Bernd Bischl (IEEE Trans. Evol. Comput., 2022)

Neural Architecture Search for Genomic Sequence Data. - Amadeu Scheppach; Hüseyin Anil Gündüz; Emilio Dorigatti; Philipp C. Münch; Alice C. McHardy; Bernd Bischl; Mina Rezaei; Martin Binder (CIBCB, 2023)

Uncertainty Quantification for Deep Learning Models Predicting the Regulatory Activity of DNA Sequences. - Hüseyin Anil Gündüz; Sheetal Giri; Martin Binder; Bernd Bischl; Mina Rezaei (ICMLA, 2023)

counterfactuals: An R Package for Counterfactual Explanation Methods. - Susanne Dandl; Andreas Hofheinz; Martin Binder; Bernd Bischl; Giuseppe Casalicchio (CoRR, 2023)

Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges. - Bernd Bischl; Martin Binder; Michel Lang; Tobias Pielok; Jakob Richter; Stefan Coors; Janek Thomas; Theresa Ullmann; Marc Becker; Anne-Laure Boulesteix; Difan Deng; Marius Lindauer (WIREs Data. Mining. Knowl. Discov., 2023)

Multi-Objective Hyperparameter Optimization in Machine Learning - An Overview. - Florian Karl; Tobias Pielok; Julia Moosbauer; Florian Pfisterer; Stefan Coors; Martin Binder; Lennart Schneider; Janek Thomas; Jakob Richter; Michel Lang; Eduardo C. Garrido-Merchán; Jürgen Branke; et al. (ACM Trans. Evol. Learn. Optim., 2023)