Giuseppe Casalicchio

71 papers A* 3A 1Journal 51Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Analyzing Error Sources in Global Feature Effect Estimation. CoRR Timo Heiß, Coco Bögel, Bernd Bischl, Giuseppe Casalicchio
2026	J	`jnl`	CASHomon Sets: Efficient Rashomon Sets Across Multiple Model Classes and their Hyperparameters. CoRR Fiona Katharina Ewald, Martin Binder, Matthias Feurer, Bernd Bischl, Giuseppe Casalicchio
2026	J	`jnl`	Interpretability-by-Design with Accurate Locally Additive Models and Conditional Feature Effects. CoRR Vasilis Gkolemis, Loukas Kavouras, Dimitrios Kyriakopoulos, Konstantinos Tsopelas, Dimitrios Rontogiannis, Giuseppe Casalicchio, Theodore Dalamagas, Christos Diou
2026	J	`jnl`	Optimal Transport Group Counterfactual Explanations. CoRR Enrique Valero-Leal, Bernd Bischl, Pedro Larrañaga, Concha Bielza, Giuseppe Casalicchio
2026	J	`jnl`	xplainfi: Feature Importance and Statistical Inference for Machine Learning in R. CoRR Lukas Burk, Fiona Katharina Ewald, Giuseppe Casalicchio, Marvin N. Wright, Bernd Bischl
2025	A*	`conf`	Efficient and Accurate Explanation Estimation with Distribution Compression. ICLR Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek
2025	—	`conf`	Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration for Exosuit Personalization. ECML/PKDD (8) Julian Rodemann, Federico Croppi, Philipp Arens, Yusuf Sale, Julia Herbinger, Bernd Bischl, Eyke Hüllermeier, Thomas Augustin, Conor J. Walsh, Giuseppe Casalicchio
2025	J	`jnl`	OpenML: Insights from 10 years and more than a thousand papers. Patterns Bernd Bischl, Giuseppe Casalicchio, Taniya Das, Matthias Feurer, Sebastian Fischer, Pieter Gijsbers, Subhaditya Mukherjee, Andreas C. Müller, László Németh, Luis Oala, Lennart Purucker, Sahithya Ravi, Jan N. van Rijn, Prabhant Singh, Joaquin Vanschoren, Jos van der Velde, Marcel Wever
2025	J	`jnl`	Privilege Scores. CoRR Ludwig Bothmann, Philip A. Boustani, José M. Álvarez, Giuseppe Casalicchio, Bernd Bischl, Susanne Dandl
2025	J	`jnl`	counterfactuals : An J. Stat. Softw. Susanne Dandl, Andreas Hofheinz, Martin Binder, Bernd Bischl, Giuseppe Casalicchio
2025	J	`jnl`	fmeffects: An R Package for Forward Marginal Effects. R J. Holger Löwe, Christian A. Scholbeck, Christian Heumann, Bernd Bischl, Giuseppe Casalicchio
2024	—	`conf`	A Guide to Feature Importance Methods for Scientific Inference. xAI (2) Fiona Katharina Ewald, Ludwig Bothmann, Marvin N. Wright, Bernd Bischl, Giuseppe Casalicchio, Gunnar König
2024	J	`jnl`	A Guide to Feature Importance Methods for Scientific Inference. CoRR Fiona Katharina Ewald, Ludwig Bothmann, Marvin N. Wright, Bernd Bischl, Giuseppe Casalicchio, Gunnar König
2024	J	`jnl`	Correction: Marginal effects for non-linear prediction functions. Data Min. Knowl. Discov. Christian A. Scholbeck, Giuseppe Casalicchio, Christoph Molnar, Bernd Bischl, Christian Heumann
2024	J	`jnl`	Decomposing Global Feature Effects Based on Feature Interactions. J. Mach. Learn. Res. Julia Herbinger, Marvin N. Wright, Thomas Nagler, Bernd Bischl, Giuseppe Casalicchio
2024	J	`jnl`	Effector: A Python package for regional explanations. CoRR Vasilis Gkolemis, Christos Diou, Eirini Ntoutsi, Theodore Dalamagas, Bernd Bischl, Julia Herbinger, Giuseppe Casalicchio
2024	J	`jnl`	Efficient and Accurate Explanation Estimation with Distribution Compression. CoRR Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek
2024	J	`jnl`	Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration. CoRR Julian Rodemann, Federico Croppi, Philipp Arens, Yusuf Sale, Julia Herbinger, Bernd Bischl, Eyke Hüllermeier, Thomas Augustin, Conor J. Walsh, Giuseppe Casalicchio
2024	J	`jnl`	Marginal effects for non-linear prediction functions. Data Min. Knowl. Discov. Christian A. Scholbeck, Giuseppe Casalicchio, Christoph Molnar, Bernd Bischl, Christian Heumann
2024	J	`jnl`	Model-agnostic feature importance and effects with dependent features: a conditional subgroup approach. Data Min. Knowl. Discov. Christoph Molnar, Gunnar König, Bernd Bischl, Giuseppe Casalicchio
2024	—	`conf`	On the Robustness of Global Feature Effect Explanations. ECML/PKDD (2) Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek
2024	J	`jnl`	On the Robustness of Global Feature Effect Explanations. CoRR Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek
2024	A*	`conf`	Position: Why We Must Rethink Empirical Research in Machine Learning. ICML Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl
2024	J	`jnl`	Position: Why We Must Rethink Empirical Research in Machine Learning. CoRR Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl
2024	—	`conf`	mlr3summary: Concise and interpretable summaries for machine learning models. xAI (Late-breaking Work, Demos, Doctoral Consortium) Susanne Dandl, Marc Becker, Bernd Bischl, Giuseppe Casalicchio, Ludwig Bothmann
2024	J	`jnl`	mlr3summary: Concise and interpretable summaries for machine learning models. CoRR Susanne Dandl, Marc Becker, Bernd Bischl, Giuseppe Casalicchio, Ludwig Bothmann
2023	—	`conf`	Algorithm-Agnostic Feature Attributions for Clustering. xAI (1) Christian A. Scholbeck, Henri Funk, Giuseppe Casalicchio
2023	J	`jnl`	Decomposing Global Feature Effects Based on Feature Interactions. CoRR Julia Herbinger, Bernd Bischl, Giuseppe Casalicchio
2023	—	`conf`	Interpretable Regional Descriptors: Hyperbox-Based Local Explanations. ECML/PKDD (3) Susanne Dandl, Giuseppe Casalicchio, Bernd Bischl, Ludwig Bothmann
2023	J	`jnl`	Interpretable Regional Descriptors: Hyperbox-Based Local Explanations. CoRR Susanne Dandl, Giuseppe Casalicchio, Bernd Bischl, Ludwig Bothmann
2023	—	`conf`	Leveraging Model-Based Trees as Interpretable Surrogate Models for Model Distillation. ECAI Workshops (1) Julia Herbinger, Susanne Dandl, Fiona Katharina Ewald, Sofia Loibl, Giuseppe Casalicchio
2023	J	`jnl`	Leveraging Model-based Trees as Interpretable Surrogate Models for Model Distillation. CoRR Julia Herbinger, Susanne Dandl, Fiona Katharina Ewald, Sofia Loibl, Giuseppe Casalicchio
2023	J	`jnl`	Position Paper: Bridging the Gap Between Machine Learning and Sensitivity Analysis. CoRR Christian A. Scholbeck, Julia Moosbauer, Giuseppe Casalicchio, Hoshin Gupta, Bernd Bischl, Christian Heumann
2023	—	`conf`	Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process. xAI (1) Christoph Molnar, Timo Freiesleben, Gunnar König, Julia Herbinger, Tim Reisinger, Giuseppe Casalicchio, Marvin N. Wright, Bernd Bischl
2023	J	`jnl`	counterfactuals: An R Package for Counterfactual Explanation Methods. CoRR Susanne Dandl, Andreas Hofheinz, Martin Binder, Bernd Bischl, Giuseppe Casalicchio
2023	J	`jnl`	fmeffects: An R Package for Forward Marginal Effects. CoRR Holger Löwe, Christian A. Scholbeck, Christian Heumann, Bernd Bischl, Giuseppe Casalicchio
2022	J	`jnl`	Algorithm-Agnostic Interpretations for Clustering. CoRR Christian A. Scholbeck, Henri Funk, Giuseppe Casalicchio
2022	—	`conf`	Developing Open Source Educational Resources for Machine Learning and Data Science. Teaching ML Ludwig Bothmann, Sven Strickroth, Giuseppe Casalicchio, David Rügamer, Marius Lindauer, Fabian Scheipl, Bernd Bischl
2022	J	`jnl`	Enhancing Explainability of Hyperparameter Optimization via Bayesian Algorithm Execution. CoRR Julia Moosbauer, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl
2022	J	`jnl`	Grouped feature importance and combined features effect plot. Data Min. Knowl. Discov. Quay Au, Julia Herbinger, Clemens Stachl, Bernd Bischl, Giuseppe Casalicchio
2022	J	`jnl`	Marginal Effects for Non-Linear Prediction Functions. CoRR Christian A. Scholbeck, Giuseppe Casalicchio, Christoph Molnar, Bernd Bischl, Christian Heumann
2022	J	`jnl`	Over-optimism in benchmark studies and the multiplicity of design and analysis options when interpreting their results. WIREs Data Mining Knowl. Discov. Christina Nießl, Moritz Herrmann, Chiara Wiedemann, Giuseppe Casalicchio, Anne-Laure Boulesteix
2022	A	`conf`	REPID: Regional Effect Plots with implicit Interaction Detection. AISTATS Julia Herbinger, Bernd Bischl, Giuseppe Casalicchio
2022	J	`jnl`	REPID: Regional Effect Plots with implicit Interaction Detection. CoRR Julia Herbinger, Bernd Bischl, Giuseppe Casalicchio
2021	J	`jnl`	Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT). CoRR Gunnar König, Timo Freiesleben, Bernd Bischl, Giuseppe Casalicchio, Moritz Grosse-Wentrup
2021	J	`jnl`	Developing Open Source Educational Resources for Machine Learning and Data Science. CoRR Ludwig Bothmann, Sven Strickroth, Giuseppe Casalicchio, David Rügamer, Marius Lindauer, Fabian Scheipl, Bernd Bischl
2021	A*	`conf`	Explaining Hyperparameter Optimization via Partial Dependence Plots. NeurIPS Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl
2021	J	`jnl`	Explaining Hyperparameter Optimization via Partial Dependence Plots. CoRR Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl
2021	J	`jnl`	Grouped Feature Importance and Combined Features Effect Plot. CoRR Quay Au, Julia Herbinger, Clemens Stachl, Bernd Bischl, Giuseppe Casalicchio
2021	—	`conf`	OpenML Benchmarking Suites. NeurIPS Datasets and Benchmarks Bernd Bischl, Giuseppe Casalicchio, Matthias Feurer, Pieter Gijsbers, Frank Hutter, Michel Lang, Rafael Gomes Mantovani, Jan N. van Rijn, Joaquin Vanschoren
2021	J	`jnl`	Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process. CoRR Christoph Molnar, Timo Freiesleben, Gunnar König, Giuseppe Casalicchio, Marvin N. Wright, Bernd Bischl
2020	—	`conf`	General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models. xxAI@ICML Christoph Molnar, Gunnar König, Julia Herbinger, Timo Freiesleben, Susanne Dandl, Christian A. Scholbeck, Giuseppe Casalicchio, Moritz Grosse-Wentrup, Bernd Bischl
2020	—	`conf`	Interpretable Machine Learning - A Brief History, State-of-the-Art and Challenges. PKDD/ECML Workshops Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl
2020	J	`jnl`	Interpretable Machine Learning - A Brief History, State-of-the-Art and Challenges. CoRR Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl
2020	J	`jnl`	Model-agnostic Feature Importance and Effects with Dependent Features - A Conditional Subgroup Approach. CoRR Christoph Molnar, Gunnar König, Bernd Bischl, Giuseppe Casalicchio
2020	J	`jnl`	Pitfalls to Avoid when Interpreting Machine Learning Models. CoRR Christoph Molnar, Gunnar König, Julia Herbinger, Timo Freiesleben, Susanne Dandl, Christian A. Scholbeck, Giuseppe Casalicchio, Moritz Grosse-Wentrup, Bernd Bischl
2019	J	`jnl`	Component-Wise Boosting of Targets for Multi-Output Prediction. CoRR Quay Au, Daniel Schalk, Giuseppe Casalicchio, Ramona Schödel, Clemens Stachl, Bernd Bischl
2019	—	`—`	On benchmark experiments and visualization methods for the evaluation and interpretation of machine learning models. Giuseppe Casalicchio
2019	J	`jnl`	OpenML: An R package to connect to the machine learning platform OpenML. Comput. Stat. Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl
2019	J	`jnl`	Quantifying Interpretability of Arbitrary Machine Learning Models Through Functional Decomposition. CoRR Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl
2019	—	`conf`	Quantifying Model Complexity via Functional Decomposition for Better Post-hoc Interpretability. PKDD/ECML Workshops (1) Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl
2019	J	`jnl`	Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model Agnostic Interpretations. CoRR Christian A. Scholbeck, Christoph Molnar, Christian Heumann, Bernd Bischl, Giuseppe Casalicchio
2019	—	`conf`	Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model-Agnostic Interpretations. PKDD/ECML Workshops (1) Christian A. Scholbeck, Christoph Molnar, Christian Heumann, Bernd Bischl, Giuseppe Casalicchio
2019	J	`jnl`	mlr3: A modern object-oriented machine learning framework in R. J. Open Source Softw. Michel Lang, Martin Binder, Jakob Richter, Patrick Schratz, Florian Pfisterer, Stefan Coors, Quay Au, Giuseppe Casalicchio, Lars Kotthoff, Bernd Bischl
2018	—	`conf`	Visualizing the Feature Importance for Black Box Models. ECML/PKDD (1) Giuseppe Casalicchio, Christoph Molnar, Bernd Bischl
2018	J	`jnl`	Visualizing the Feature Importance for Black Box Models. CoRR Giuseppe Casalicchio, Christoph Molnar, Bernd Bischl
2018	J	`jnl`	iml: An R package for Interpretable Machine Learning. J. Open Source Softw. Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl
2017	J	`jnl`	Multilabel Classification with R Package mlr. R J. Philipp Probst, Quay Au, Giuseppe Casalicchio, Clemens Stachl, Bernd Bischl
2017	J	`jnl`	OpenML Benchmarking Suites and the OpenML100. CoRR Bernd Bischl, Giuseppe Casalicchio, Matthias Feurer, Frank Hutter, Michel Lang, Rafael Gomes Mantovani, Jan N. van Rijn, Joaquin Vanschoren
2017	J	`jnl`	OpenML: An R Package to Connect to the Networked Machine Learning Platform OpenML. CoRR Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl
2016	J	`jnl`	mlr: Machine Learning in R. J. Mach. Learn. Res. Bernd Bischl, Michel Lang, Lars Kotthoff, Julia Schiffner, Jakob Richter, Erich Studerus, Giuseppe Casalicchio, Zachary M. Jones