| 2.5 Survival Prediction and Model Selection J Rahnenführer, M Lang, J Richter Machine Learning under Resource Constraints-Applications, 71, 2022 | | 2022 |
| A NOVEL, COMPREHENSIVE IN SILICO MODEL FOR RESPIRATORY DRUG DELIVERY M Grill, KR Wichmann, D Rudlstorfer, M Rixner, M Brei, J Richter, ... JOURNAL OF AEROSOL MEDICINE AND PULMONARY DRUG DELIVERY 36 (6), A21-A22, 2023 | | 2023 |
| A probabilistic neural twin for treatment planning in peripheral pulmonary artery stenosis JD Lee, J Richter, MR Pfaller, JM Szafron, K Menon, A Zanoni, MR Ma, ... International journal for numerical methods in biomedical engineering, e3820, 2024 | | 2024 |
| Analysing geo data on a street level performed on an example of road accidents in London J Richter | | |
| Bayesian Windkessel calibration using optimized 0D surrogate models J Richter, J Nitzler, L Pegolotti, K Menon, J Biehler, WA Wall, ... arXiv preprint arXiv:2404.14187, 2024 | | 2024 |
| BBmisc: Miscellaneous helper functions for B B Bischl, M Lang, J Bossek, D Horn, J Richter, D Surmann Bischl. R package version 1, 2017, 2017 | 26 | 2017 |
| BBmisc: Miscellaneous helper functions for B. Bischl B Bischl, M Lang, J Bossek, D Horn, J Richter, D Surmann R package version 1.11, 2017 | 27 | 2017 |
| Evolutionary Learning and Optimization J Renzullo, W Weimer, S Forrest, D Yazdani, MN Omidvar, AH Gandomi, ... ACM Transactions on 3 (4), 2023 | | 2023 |
| Extending Model-Based Optimization with Resource-Aware Parallelization and for Dynamic Optimization Problems J Richter TU Dortmund, 2020 | | 2020 |
| Faster Model Based Optimization through Resource Aware Scheduling J Richter Technical report for Collaborative Research Center SFB 876 Providing …, 2015 | | 2015 |
| Faster Model Based Optimization through Resource Aware Scheduling and asynchronous Evaluations J Richter Technical report for Collaborative Research Center SFB 876 Providing …, 2016 | | 2016 |
| Faster model-based optimization through resource-aware scheduling strategies J Richter, H Kotthaus, B Bischl, P Marwedel, J Rahnenführer, M Lang Learning and Intelligent Optimization: 10th International Conference, LION …, 2016 | 20 | 2016 |
| 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 | 373 | 2023 |
| Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data P Schratz, J Muenchow, E Iturritxa, J Richter, A Brenning Ecological Modelling 406, 109-120, 2019 | 375 | 2019 |
| Improving adaptive seamless designs through Bayesian optimization J Richter, T Friede, J Rahnenführer Biometrical Journal 64 (5), 948-963, 2022 | 8 | 2022 |
| In silico high-resolution whole lung model to predict the locally delivered dose of inhaled drugs MJ Grill, J Biehler, KR Wichmann, D Rudlstorfer, M Rixner, M Brei, ... arXiv preprint arXiv:2307.04757, 2023 | 2 | 2023 |
| Machine Learning in R M Lang, J Richter | 1 | 2019 |
| mlr Tutorial J Schiffner, B Bischl, M Lang, J Richter, ZM Jones, P Probst, F Pfisterer, ... arXiv preprint arXiv:1609.06146, 2016 | 9 | 2016 |
| mlr: Machine Learning in R B Bischl, M Lang, L Kotthoff, J Schiffner, J Richter, E Studerus, ... Journal of Machine Learning Research 17 (170), 1-5, 2016 | 919 | 2016 |
| mlr3 book M Becker, M Binder, B Bischl, N Foss, L Kotthoff, M Lan, F Pfisterer, ... URl: https://mlr3book. mlr-org. com 28, 29-30, 2021 | 12 | 2021 |
Michel LangTU Dortmund; LMU MunichVerified email at statistik.tu-dortmund.de