| mlr3: A modern object-oriented machine learning framework in R M Lang, M Binder, J Richter, P Schratz, F Pfisterer, S Coors, Q Au, ... Journal of Open Source Software 4 (44), 1903, 2019 | 221 | 2019 |
| Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges B Bischl, M Binder, M Lang, T Pielok, J Richter, S Coors, J Thomas, ... Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 13 (2 …, 2023 | 156 | 2023 |
| Automatic gradient boosting J Thomas, S Coors, B Bischl arXiv preprint arXiv:1807.03873, 2018 | 33 | 2018 |
| mlr3: A modern object-oriented machine learning framework in RJ Open Source Softw M Lang, M Binder, J Richter, P Schratz, F Pfisterer, S Coors, Q Au, ... | 28 | 2019 |
| Amlb: an automl benchmark P Gijsbers, MLP Bueno, S Coors, E LeDell, S Poirier, J Thomas, B Bischl, ... arXiv preprint arXiv:2207.12560, 2022 | 22 | 2022 |
| Machine learning for the educational sciences S Hilbert, S Coors, E Kraus, B Bischl, A Lindl, M Frei, J Wild, S Krauss, ... Review of Education 9 (3), e3310, 2021 | 19 | 2021 |
| Multi-Objective Hyperparameter Optimization--An Overview F Karl, T Pielok, J Moosbauer, F Pfisterer, S Coors, M Binder, L Schneider, ... arXiv preprint arXiv:2206.07438, 2022 | 16 | 2022 |
| Multi-objective automatic machine learning with autoxgboostmc F Pfisterer, S Coors, J Thomas, B Bischl arXiv preprint arXiv:1908.10796, 2019 | 14 | 2019 |
| Hyperparameter optimization: Foundations, algorithms, best practices and open challenges. arXiv 2021 B Bischl, M Binder, M Lang, T Pielok, J Richter, S Coors, J Thomas, ... arXiv preprint arXiv:2107.05847, 0 | 10 | |
| Predicting instructed simulation and dissimulation when screening for depressive symptoms S Goerigk, S Hilbert, A Jobst, P Falkai, M Bühner, C Stachl, B Bischl, ... European Archives of Psychiatry and Clinical Neuroscience 270, 153-168, 2020 | 7 | 2020 |
| Hyperparameter optimization: foundations, algorithms, best practices and open challenges (2021a) B Bischl, M Binder, M Lang, T Pielok, J Richter, S Coors, J Thomas, ... arXiv preprint arXiv:2107.05847, 0 | 6 | |
| mlr3: Machine learning in R—Next generation M Lang, B Bischl, J Richter, P Schratz, G Casalicchio, S Coors, Q Au, ... R Package Version 0.13. 0. Available online: https://CRAN. R-project. org …, 2021 | 5 | 2021 |
| Automatic Componentwise Boosting: An Interpretable AutoML System S Coors, D Schalk, B Bischl, D Rügamer arXiv preprint arXiv:2109.05583, 2021 | 3 | 2021 |
| Automatic gradient boosting S Coors | 3 | 2018 |
| Machine learning for spelling acquisition-How accurate is the prediction of specific spelling errors in German primary school students? R Böhme, S Coors, P Oster, M Munser-Kiefer, S Hilbert PsyArXiv, 2022 | 1 | 2022 |
| A Comprehensive Machine Learning Benchmark Study for Radiomics-Based Survival Analysis of CT Imaging Data in Patients With Hepatic Metastases of CRC AT Stüber, S Coors, B Schachtner, T Weber, D Rügamer, A Bender, ... Investigative Radiology 58 (12), 874-881, 2023 | | 2023 |
| Revitalize the Potential of Radiomics: Interpretation and Feature Stability in Medical Imaging Analyses through Groupwise Feature Importance AT Stüber, S Coors, M Ingrisch | | 2023 |
| Multi-Objective Hyperparameter Optimization in Machine Learning–An Overview F Karl, T Pielok, J Moosbauer, F Pfisterer, S Coors, M Binder, L Schneider, ... ACM Transactions on Evolutionary Learning, 2023 | | 2023 |
Bernd BischlChair of Statistical Learning and Data Science, LMU MunichVerified email at stat.uni-muenchen.de
