Susanne Dandl - RankMe

20 papers Journal 11Unranked 8

Year	Rank	Type	Title / Venue / Authors
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
2024	—	`conf`	CountARFactuals - Generating Plausible Model-Agnostic Counterfactual Explanations with Adversarial Random Forests. xAI (3) Susanne Dandl, Kristin Blesch, Timo Freiesleben, Gunnar König, Jan Kapar, Bernd Bischl, Marvin N. Wright
2024	J	`jnl`	CountARFactuals - Generating plausible model-agnostic counterfactual explanations with adversarial random forests. CoRR Susanne Dandl, Kristin Blesch, Timo Freiesleben, Gunnar König, Jan Kapar, Bernd Bischl, Marvin N. Wright
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`	Causal Fair Machine Learning via Rank-Preserving Interventional Distributions. AEQUITAS@ECAI Ludwig Bothmann, Susanne Dandl, Michael Schomaker
2023	J	`jnl`	Causal Fair Machine Learning via Rank-Preserving Interventional Distributions. CoRR Ludwig Bothmann, Susanne Dandl, Michael Schomaker
2023	—	`—`	Causality concepts in machine learning: heterogeneous treatment effect estimation with machine learning & model interpretation with counterfactual and semi-factual explanations. Susanne Dandl
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`	counterfactuals: An R Package for Counterfactual Explanation Methods. CoRR Susanne Dandl, Andreas Hofheinz, Martin Binder, Bernd Bischl, Giuseppe Casalicchio
2022	—	`conf`	Multi-objective counterfactual fairness. GECCO Companion Susanne Dandl, Florian Pfisterer, Bernd Bischl
2021	J	`jnl`	mcboost: Multi-Calibration Boosting for R. J. Open Source Softw. Florian Pfisterer, Christoph Kern, Susanne Dandl, Matthew Sun, Michael P. Kim, 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`	Multi-Objective Counterfactual Explanations. PPSN (1) Susanne Dandl, Christoph Molnar, Martin Binder, Bernd Bischl
2020	J	`jnl`	Multi-Objective Counterfactual Explanations. CoRR Susanne Dandl, Christoph Molnar, Martin Binder, Bernd Bischl
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