Bernd Bischl

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Citations	8752	7679
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Michel LangTU Dortmund; LMU MunichVerified email at statistik.tu-dortmund.de
Giuseppe CasalicchioPostdoctoral Researcher, LMU Munich, Munich Center for Machine LearningVerified email at campus.lmu.de
Janek ThomasLudwig-Maximilians-University MunichVerified email at stat.uni-muenchen.de
Joaquin VanschorenEindhoven University of TechnologyVerified email at tue.nl
Florian PfistererLudwig Maximilian University of MunichVerified email at stat.uni-muenchen.de
Jakob RichterTU DortmundVerified email at statistik.tu-dortmund.de
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Olaf MersmannTH KölnVerified email at p-value.net
Heike TrautmannProfessor of Data Science: Statistics and Optimization, Department of Information SystemsVerified email at wi.uni-muenster.de
Jan N. van RijnLeiden UniversityVerified email at liacs.leidenuniv.nl
David RügamerAssociate Professor for Data Science, LMU MunichVerified email at stat.uni-muenchen.de
Daniel HornStatistical Methods for Big Data, TU DortmundVerified email at tu-dortmund.de
Quay AuMember of "Computational Statistics" Group, LMU MunichVerified email at stat.uni-muenchen.de
Clemens StachlAssociate Professor of Behavioral Science, University of St. GallenVerified email at unisg.ch
Jakob BossekRWTH Aachen UniversityVerified email at aim.rwth-aachen.de
Stefan CoorsComputational Statistics, Ludwig-Maximilians Unversity MunichVerified email at campus.lmu.de
Xudong SunKTH Royal Institute of TechnologyVerified email at kth.se
Jörg RahnenführerTU Dortmund UniversityVerified email at statistik.tu-dortmund.de
Philipp ProbstVerified email at digital-ratio.de
Mike PreussUniversiteit LeidenVerified email at liacs.leidenuniv.nl

Bernd Bischl

Chair of Statistical Learning and Data Science, LMU Munich

Verified email at stat.uni-muenchen.de - Homepage

Machine Learning Statistics Data Science Statistical Learning Scientific Software


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OpenML: networked science in machine learning J Vanschoren, JN Van Rijn, B Bischl, L Torgo ACM SIGKDD Explorations Newsletter 15 (2), 49-60, 2014	1123	2014
mlr: Machine Learning in R B Bischl, M Lang, L Kotthoff, J Schiffner, J Richter, E Studerus, ... The Journal of Machine Learning Research 17 (1), 5938-5942, 2016	777	2016
Tunability: Importance of hyperparameters of machine learning algorithms P Probst, AL Boulesteix, B Bischl The Journal of Machine Learning Research 20 (1), 1934-1965, 2019	548	2019
Benchmark for filter methods for feature selection in high-dimensional classification data A Bommert, X Sun, B Bischl, J Rahnenführer, M Lang Computational Statistics & Data Analysis 143, 106839, 2020	377	2020
Interpretable machine learning–a brief history, state-of-the-art and challenges C Molnar, G Casalicchio, B Bischl ECML PKDD 2020 Workshops: Workshops of the European Conference on Machine …, 2021	328	2021
Exploratory landscape analysis O Mersmann, B Bischl, H Trautmann, M Preuss, C Weihs, G Rudolph Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011	324	2011
iml: An R package for interpretable machine learning C Molnar, G Casalicchio, B Bischl Journal of Open Source Software 3 (26), 786, 2018	288	2018
Predicting personality from patterns of behavior collected with smartphones C Stachl, Q Au, R Schoedel, SD Gosling, GM Harari, D Buschek, ... Proceedings of the National Academy of Sciences 117 (30), 17680-17687, 2020	231*	2020
Amlb: an automl benchmark P Gijsbers, MLP Bueno, S Coors, E LeDell, S Poirier, J Thomas, B Bischl, ... arXiv preprint arXiv:2207.12560, 2022	229*	2022
Aslib: A benchmark library for algorithm selection B Bischl, P Kerschke, L Kotthoff, M Lindauer, Y Malitsky, A Fréchette, ... Artificial Intelligence 237, 41-58, 2016	220	2016
mlrMBO: A modular framework for model-based optimization of expensive black-box functions B Bischl, J Richter, J Bossek, D Horn, J Thomas, M Lang arXiv preprint arXiv:1703.03373, 2017	190*	2017
Resampling methods for meta-model validation with recommendations for evolutionary computation B Bischl, O Mersmann, H Trautmann, C Weihs Evolutionary computation 20 (2), 249-275, 2012	189	2012
Multi-objective counterfactual explanations S Dandl, C Molnar, M Binder, B Bischl Parallel Problem Solving from Nature–PPSN XVI: 16th International Conference …, 2020	178	2020
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	175	2019
Visualizing the feature importance for black box models G Casalicchio, C Molnar, B Bischl Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019	166	2019
Algorithm selection based on exploratory landscape analysis and cost-sensitive learning B Bischl, O Mersmann, H Trautmann, M Preuß Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012	158	2012
Personality traits predict smartphone usage C Stachl, S Hilbert, JQ Au, D Buschek, A De Luca, B Bischl, H Hussmann, ... European Journal of Personality 31 (6), 701-722, 2017	142	2017
Openml benchmarking suites B Bischl, G Casalicchio, M Feurer, P Gijsbers, F Hutter, M Lang, ... arXiv preprint arXiv:1708.03731, 2017	119	2017
Effectiveness of random search in SVM hyper-parameter tuning RG Mantovani, ALD Rossi, J Vanschoren, B Bischl, AC De Carvalho 2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015	116	2015
Robust anomaly detection in images using adversarial autoencoders L Beggel, M Pfeiffer, B Bischl Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020	101	2020

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