Giuseppe Casalicchio

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Bernd BischlChair of Statistical Learning and Data Science, LMU MunichVerified email at stat.uni-muenchen.de
Michel LangTU Dortmund; LMU MunichVerified email at statistik.tu-dortmund.de
Joaquin VanschorenEindhoven University of TechnologyVerified email at tue.nl
Jakob RichterTU DortmundVerified email at statistik.tu-dortmund.de
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Jan N. van RijnLeiden UniversityVerified email at liacs.leidenuniv.nl
Quay AuMember of "Computational Statistics" Group, LMU MunichVerified email at stat.uni-muenchen.de
Zachary M. JonesMetaVerified email at fb.com
Gunnar KönigPhD Candidate, LMU Munich/MCML; Research Fellow, University of ViennaVerified email at stat.uni-muenchen.de
Christian A. ScholbeckResearch Associate at Ludwig-Maximilians-Universität (LMU) MunichVerified email at stat.uni-muenchen.de
Erich StuderusLecturer and researcher at the University of Basel, Department of PsychologyVerified email at unibas.ch
Clemens StachlAssociate Professor of Behavioral Science, University of St. GallenVerified email at unisg.ch
Matthias FeurerMachine Learning group, University of FreiburgVerified email at informatik.uni-freiburg.de
Andreas BenderLudwig-Maximilians-Universität MünchenVerified email at stat.uni-muenchen.de
Jakob BossekRWTH Aachen UniversityVerified email at aim.rwth-aachen.de
Stefan CoorsComputational Statistics, Ludwig-Maximilians Unversity MunichVerified email at campus.lmu.de
Helmut KüchenhoffInstitut für Statistik, LMU MünchenVerified email at stat.uni-muenchen.de
Rafael Gomes MantovaniFederal Technology University - Paraná, campus of ApucaranaVerified email at utfpr.edu.br
Frank HutterProfessor of Computer Science, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
Pascal KerschkeProfessor of Big Data Analytics in Transportation, TU Dresden, GermanyVerified email at tu-dresden.de

Giuseppe Casalicchio

Postdoctoral Researcher, LMU Munich, Munich Center for Machine Learning

Verified email at campus.lmu.de - Homepage

Machine Learning xAI Explainable AI interpretability Interpretable Machine Learning


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OpenML: A networked science platform for machine learning J Vanschoren, JN van Rijn, B Bischl, G Casalicchio, M Lang, M Feurer 2015 ICML Workshop on Machine Learning Open Source Software (MLOSS 2015)., 2015	1055*	2015
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	783	2016
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	279	2021
iml: An R package for interpretable machine learning C Molnar, G Casalicchio, B Bischl Journal of Open Source Software 3 (26), 786, 2018	270	2018
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	159	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	155	2019
OpenML Benchmarking Suites B Bischl, G Casalicchio, M Feurer, P Gijsbers, F Hutter, M Lang, ... NeurIPS 2021 Datasets and Benchmarks Track, 2021	106*	2021
Quantifying model complexity via functional decomposition for better post-hoc interpretability C Molnar, G Casalicchio, B Bischl Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2019, 193--204, 2019	62*	2019
OpenML: An R package to connect to the machine learning platform OpenML G Casalicchio, J Bossek, M Lang, D Kirchhoff, P Kerschke, B Hofner, ... Computational Statistics 34, 977-991, 2019	61	2019
General pitfalls of model-agnostic interpretation methods for machine learning models C Molnar, G König, J Herbinger, T Freiesleben, S Dandl, CA Scholbeck, ... xxAI-Beyond Explainable AI: International Workshop, Held in Conjunction with …, 2022	42	2022
Pitfalls to avoid when interpreting machine learning models C Molnar, G König, J Herbinger, T Freiesleben, S Dandl, CA Scholbeck, ... Accepted at the ICML 2020 workshop XXAI: Extending Explainable AI Beyond …, 2020	41	2020
Model-agnostic feature importance and effects with dependent features: a conditional subgroup approach C Molnar, G König, B Bischl, G Casalicchio Data Mining and Knowledge Discovery, 1-39, 2023	38	2023
Prevalence and severity of foot pad alterations in German turkey poults during the early rearing phase S Bergmann, N Ziegler, T Bartels, J Hübel, C Schumacher, E Rauch, ... Poultry science 92 (5), 1171-1176, 2013	31	2013
Multilabel classification with R package mlr P Probst, Q Au, G Casalicchio, C Stachl, B Bischl The R Journal 9 (1), 352-369, 2017	25	2017
Relating the partial dependence plot and permutation feature importance to the data generating process C Molnar, T Freiesleben, G König, G Casalicchio, MN Wright, B Bischl arXiv preprint arXiv:2109.01433, 2021	22	2021
Sampling, intervention, prediction, aggregation: A generalized framework for model-agnostic interpretations CA Scholbeck, C Molnar, C Heumann, B Bischl, G Casalicchio Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2019, 205--216, 2019	22	2019
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	20*	2021
Nonlinear analysis to detect if excellent nursing work environments have highest well‐being G Casalicchio, E Lesaffre, H Küchenhoff, L Bruyneel Journal of nursing scholarship 49 (5), 537-547, 2017	17	2017
Grouped feature importance and combined features effect plot Q Au, J Herbinger, C Stachl, B Bischl, G Casalicchio arXiv preprint arXiv:2104.11688, 2021	14	2021
Over‐optimism in benchmark studies and the multiplicity of design and analysis options when interpreting their results C Nießl, M Herrmann, C Wiedemann, G Casalicchio, AL Boulesteix Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 12 (2 …, 2022	11	2022

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