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Julia Moosbauer
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Explaining hyperparameter optimization via partial dependence plots
J Moosbauer, J Herbinger, G Casalicchio, M Lindauer, B Bischl
Advances in Neural Information Processing Systems 34, 2280-2291, 2021
552021
Multi-objective hyperparameter tuning and feature selection using filter ensembles
M Binder, J Moosbauer, J Thomas, B Bischl
Proceedings of the 2020 genetic and evolutionary computation conference, 471-479, 2020
532020
Yahpo gym-an efficient multi-objective multi-fidelity benchmark for hyperparameter optimization
F Pfisterer, L Schneider, J Moosbauer, M Binder, B Bischl
International Conference on Automated Machine Learning, 3/1-39, 2022
392022
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
202022
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 and Optimization 3 (4), 1-50, 2023
112023
Automated benchmark-driven design and explanation of hyperparameter optimizers
J Moosbauer, M Binder, L Schneider, F Pfisterer, M Becker, M Lang, ...
IEEE Transactions on Evolutionary Computation 26 (6), 1336-1350, 2022
92022
Improving accuracy of interpretability measures in hyperparameter optimization via Bayesian algorithm execution
J Moosbauer, G Casalicchio, M Lindauer, B Bischl
arXiv preprint arXiv:2206.05447, 2022
72022
Towards explaining hyperparameter optimization via partial dependence plots
J Moosbauer, J Herbinger, G Casalicchio, M Lindauer, B Bischl
8th ICML Workshop on Automated Machine Learning (AutoML), 2020
72020
Longitudinal assessment of multiple sclerosis lesion load with synthetic magnetic resonance imaging—a multicenter validation study
S Schlaeger, HB Li, T Baum, C Zimmer, J Moosbauer, S Byas, M Mühlau, ...
Investigative Radiology 58 (5), 320-326, 2023
62023
Faster and better: how anomaly detection can accelerate and improve reporting of head computed tomography
T Finck, J Moosbauer, M Probst, S Schlaeger, M Schuberth, D Schinz, ...
Diagnostics 12 (2), 452, 2022
52022
Automated pathology detection and patient triage in routinely acquired head computed tomography scans
T Finck, D Schinz, L Grundl, R Eisawy, M Yigitsoy, J Moosbauer, F Pfister, ...
Investigative Radiology 56 (9), 571-578, 2021
52021
Automated Detection of Ischemic Stroke and Subsequent Patient Triage in Routinely Acquired Head CT
T Finck, D Schinz, L Grundl, R Eisawy, M Yiğitsoy, J Moosbauer, ...
Clinical Neuroradiology 32 (2), 419-426, 2022
22022
Position: A Call to Action for a Human-Centered AutoML Paradigm
M Lindauer, F Karl, A Klier, J Moosbauer, A Tornede, A Mueller, F Hutter, ...
arXiv preprint arXiv:2406.03348, 2024
2024
Optimized model architectures for deep learning on genomic data
HA Gündüz, R Mreches, J Moosbauer, G Robertson, XY To, EA Franzosa, ...
Communications Biology 7 (1), 516, 2024
2024
Author Correction: Optimized model architectures for deep learning on genomic data
HA Gündüz, R Mreches, J Moosbauer, G Robertson, XY To, EA Franzosa, ...
Communications Biology 7, 2024
2024
Position Paper: Bridging the Gap Between Machine Learning and Sensitivity Analysis
CA Scholbeck, J Moosbauer, G Casalicchio, H Gupta, B Bischl, ...
arXiv preprint arXiv:2312.13234, 2023
2023
Towards explainable automated machine learning
J Moosbauer
lmu, 2023
2023
Optimized model architectures for deep learning on genomic data
P Münch, HA Gündüz, R Mreches, J Moosbauer, G Robertson, XY To, ...
2023
A platform for deep learning on (meta) genomic sequences
P Münch, R Mreches, XY To, HA Gündüz, J Moosbauer, S Klawitter, ...
2023
Evolutionary Learning and Optimization
J Renzullo, W Weimer, S Forrest, D Yazdani, MN Omidvar, AH Gandomi, ...
ACM Transactions on 3 (4), 2023
2023
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