Giuseppe Casalicchio

ORCID

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 51

Top Venues

CoRR

PKDD/ECML Workshops (1)

J. Open Source Softw.

xAI (1)

Ludwig Maximilian University of Munich, Germany (PHD)

Education History

Ludwig Maximilian University of Munich, Germany

PHD

Publications

Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek
On the Robustness of Global Feature Effect Explanations. CoRR (2024)
Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek
Efficient and Accurate Explanation Estimation with Distribution Compression. CoRR (2024)
Julian Rodemann, Federico Croppi, Philipp Arens, Yusuf Sale, Julia Herbinger, Bernd Bischl, Eyke Hüllermeier, Thomas Augustin, Conor J. Walsh, Giuseppe Casalicchio
Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration. CoRR (2024)
Vasilis Gkolemis, Christos Diou, Eirini Ntoutsi, Theodore Dalamagas, Bernd Bischl, Julia Herbinger, Giuseppe Casalicchio
Effector: A Python package for regional explanations. CoRR (2024)
Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl
Position: Why We Must Rethink Empirical Research in Machine Learning. CoRR (2024)
Fiona Katharina Ewald, Ludwig Bothmann, Marvin N. Wright, Bernd Bischl, Giuseppe Casalicchio, Gunnar König
A Guide to Feature Importance Methods for Scientific Inference. CoRR (2024)
Susanne Dandl, Marc Becker, Bernd Bischl, Giuseppe Casalicchio, Ludwig Bothmann
mlr3summary: Concise and interpretable summaries for machine learning models. CoRR (2024)
Susanne Dandl, Giuseppe Casalicchio, Bernd Bischl, Ludwig Bothmann
Interpretable Regional Descriptors: Hyperbox-Based Local Explanations. CoRR (2023)
Julia Herbinger, Bernd Bischl, Giuseppe Casalicchio
Decomposing Global Feature Effects Based on Feature Interactions. CoRR (2023)
Christoph Molnar, Timo Freiesleben, Gunnar König, Julia Herbinger, Tim Reisinger, Giuseppe Casalicchio, Marvin N. Wright, Bernd Bischl
Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process. xAI (1) (2023)
Julia Herbinger, Susanne Dandl, Fiona K. Ewald, Sofia Loibl, Giuseppe Casalicchio
Leveraging Model-Based Trees as Interpretable Surrogate Models for Model Distillation. ECAI Workshops (1) (2023)
Christian A. Scholbeck, Julia Moosbauer, Giuseppe Casalicchio, Hoshin Gupta, Bernd Bischl, Christian Heumann
Position Paper: Bridging the Gap Between Machine Learning and Sensitivity Analysis. CoRR (2023)
Julia Herbinger, Susanne Dandl, Fiona K. Ewald, Sofia Loibl, Giuseppe Casalicchio
Leveraging Model-based Trees as Interpretable Surrogate Models for Model Distillation. CoRR (2023)
Susanne Dandl, Andreas Hofheinz, Martin Binder, Bernd Bischl, Giuseppe Casalicchio
counterfactuals: An R Package for Counterfactual Explanation Methods. CoRR (2023)
Christian A. Scholbeck, Henri Funk, Giuseppe Casalicchio
Algorithm-Agnostic Feature Attributions for Clustering. xAI (1) (2023)
Holger Löwe, Christian A. Scholbeck, Christian Heumann, Bernd Bischl, Giuseppe Casalicchio
fmeffects: An R Package for Forward Marginal Effects. CoRR (2023)
Susanne Dandl, Giuseppe Casalicchio, Bernd Bischl, Ludwig Bothmann
Interpretable Regional Descriptors: Hyperbox-Based Local Explanations. ECML/PKDD (3) (2023)
Julia Moosbauer, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl
Enhancing Explainability of Hyperparameter Optimization via Bayesian Algorithm Execution. CoRR (2022)
Christina Nießl, Moritz Herrmann, Chiara Wiedemann, Giuseppe Casalicchio, Anne-Laure Boulesteix
Over-optimism in benchmark studies and the multiplicity of design and analysis options when interpreting their results. WIREs Data Mining Knowl. Discov. 12 (2) (2022)
Christian A. Scholbeck, Giuseppe Casalicchio, Christoph Molnar, Bernd Bischl, Christian Heumann
Marginal Effects for Non-Linear Prediction Functions. CoRR (2022)
Ludwig Bothmann, Sven Strickroth, Giuseppe Casalicchio, David Rügamer, Marius Lindauer, Fabian Scheipl, Bernd Bischl
Developing Open Source Educational Resources for Machine Learning and Data Science. Teaching ML (2022)
Christian A. Scholbeck, Henri Funk, Giuseppe Casalicchio
Algorithm-Agnostic Interpretations for Clustering. CoRR (2022)
Julia Herbinger, Bernd Bischl, Giuseppe Casalicchio
REPID: Regional Effect Plots with implicit Interaction Detection. AISTATS (2022)
Julia Herbinger, Bernd Bischl, Giuseppe Casalicchio
REPID: Regional Effect Plots with implicit Interaction Detection. CoRR (2022)
Quay Au, Julia Herbinger, Clemens Stachl, Bernd Bischl, Giuseppe Casalicchio
Grouped feature importance and combined features effect plot. Data Min. Knowl. Discov. 36 (4) (2022)
Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl
Explaining Hyperparameter Optimization via Partial Dependence Plots. CoRR (2021)
Quay Au, Julia Herbinger, Clemens Stachl, Bernd Bischl, Giuseppe Casalicchio
Grouped Feature Importance and Combined Features Effect Plot. CoRR (2021)
Bernd Bischl, Giuseppe Casalicchio, Matthias Feurer, Pieter Gijsbers, Frank Hutter, Michel Lang, Rafael Gomes Mantovani, Jan N. van Rijn, Joaquin Vanschoren
OpenML Benchmarking Suites. NeurIPS Datasets and Benchmarks (2021)
Christoph Molnar, Timo Freiesleben, Gunnar König, Giuseppe Casalicchio, Marvin N. Wright, Bernd Bischl
Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process. CoRR (2021)
Gunnar König, Timo Freiesleben, Bernd Bischl, Giuseppe Casalicchio, Moritz Grosse-Wentrup
Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT). CoRR (2021)
Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl
Explaining Hyperparameter Optimization via Partial Dependence Plots. NeurIPS (2021)
Ludwig Bothmann, Sven Strickroth, Giuseppe Casalicchio, David Rügamer, Marius Lindauer, Fabian Scheipl, Bernd Bischl
Developing Open Source Educational Resources for Machine Learning and Data Science. CoRR (2021)
Christoph Molnar, Gunnar König, Julia Herbinger, Timo Freiesleben, Susanne Dandl, Christian A. Scholbeck, Giuseppe Casalicchio, Moritz Grosse-Wentrup, Bernd Bischl
General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models. xxAI@ICML (2020)
Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl
Interpretable Machine Learning - A Brief History, State-of-the-Art and Challenges. CoRR (2020)
Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl
Interpretable Machine Learning - A Brief History, State-of-the-Art and Challenges. PKDD/ECML Workshops (2020)
Christoph Molnar, Gunnar König, Julia Herbinger, Timo Freiesleben, Susanne Dandl, Christian A. Scholbeck, Giuseppe Casalicchio, Moritz Grosse-Wentrup, Bernd Bischl
Pitfalls to Avoid when Interpreting Machine Learning Models. CoRR (2020)
Christoph Molnar, Gunnar König, Bernd Bischl, Giuseppe Casalicchio
Model-agnostic Feature Importance and Effects with Dependent Features - A Conditional Subgroup Approach. CoRR (2020)
Christian A. Scholbeck, Christoph Molnar, Christian Heumann, Bernd Bischl, Giuseppe Casalicchio
Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model Agnostic Interpretations. CoRR (2019)
Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl
Quantifying Interpretability of Arbitrary Machine Learning Models Through Functional Decomposition. CoRR (2019)
Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl
Quantifying Model Complexity via Functional Decomposition for Better Post-hoc Interpretability. PKDD/ECML Workshops (1) (2019)
Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl
OpenML: An R package to connect to the machine learning platform OpenML. Comput. Stat. 34 (3) (2019)
Quay Au, Daniel Schalk, Giuseppe Casalicchio, Ramona Schödel, Clemens Stachl, Bernd Bischl
Component-Wise Boosting of Targets for Multi-Output Prediction. CoRR (2019)
Christian A. Scholbeck, Christoph Molnar, Christian Heumann, Bernd Bischl, Giuseppe Casalicchio
Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model-Agnostic Interpretations. PKDD/ECML Workshops (1) (2019)
Michel Lang, Martin Binder, Jakob Richter, Patrick Schratz, Florian Pfisterer, Stefan Coors, Quay Au, Giuseppe Casalicchio, Lars Kotthoff, Bernd Bischl
mlr3: A modern object-oriented machine learning framework in R. J. Open Source Softw. 4 (44) (2019)
Giuseppe Casalicchio, Christoph Molnar, Bernd Bischl
Visualizing the Feature Importance for Black Box Models. ECML/PKDD (1) (2018)
Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl
iml: An R package for Interpretable Machine Learning. J. Open Source Softw. 3 (26) (2018)
Giuseppe Casalicchio, Christoph Molnar, Bernd Bischl
Visualizing the Feature Importance for Black Box Models. CoRR (2018)
Philipp Probst, Quay Au, Giuseppe Casalicchio, Clemens Stachl, Bernd Bischl
Multilabel Classification with R Package mlr. R J. 9 (1) (2017)
Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl
OpenML: An R Package to Connect to the Networked Machine Learning Platform OpenML. CoRR (2017)
Bernd Bischl, Giuseppe Casalicchio, Matthias Feurer, Frank Hutter, Michel Lang, Rafael Gomes Mantovani, Jan N. van Rijn, Joaquin Vanschoren
OpenML Benchmarking Suites and the OpenML100. CoRR (2017)
Bernd Bischl, Michel Lang, Lars Kotthoff, Julia Schiffner, Jakob Richter, Erich Studerus, Giuseppe Casalicchio, Zachary M. Jones
mlr: Machine Learning in R. J. Mach. Learn. Res. 17 (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Giuseppe Casalicchio