General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models. - Christoph Molnar; Gunnar König; Julia Herbinger; Timo Freiesleben; Susanne Dandl; Christian A. Scholbeck; Giuseppe Casalicchio; Moritz Grosse-Wentrup; Bernd Bischl (xxAI@ICML, 2020)

Relative Feature Importance. - Gunnar König; Christoph Molnar; Bernd Bischl; Moritz Grosse-Wentrup (ICPR, 2020)

Pitfalls to Avoid when Interpreting Machine Learning Models. - Christoph Molnar; Gunnar König; Julia Herbinger; Timo Freiesleben; Susanne Dandl; Christian A. Scholbeck; Giuseppe Casalicchio; Moritz Grosse-Wentrup; Bernd Bischl (CoRR, 2020)

Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT). - Gunnar König; Timo Freiesleben; Bernd Bischl; Giuseppe Casalicchio; Moritz Grosse-Wentrup (CoRR, 2021)

A Causal Perspective on Meaningful and Robust Algorithmic Recourse. - Gunnar König; Timo Freiesleben; Moritz Grosse-Wentrup (CoRR, 2021)

Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process. - Christoph Molnar; Timo Freiesleben; Gunnar König; Giuseppe Casalicchio; Marvin N. Wright; Bernd Bischl (CoRR, 2021)

Improvement-Focused Causal Recourse (ICR). - Gunnar König; Timo Freiesleben; Moritz Grosse-Wentrup (AAAI, 2023)

Efficient SAGE Estimation via Causal Structure Learning. - Christoph Luther; Gunnar König; Moritz Grosse-Wentrup (AISTATS, 2023)

Dear XAI Community, We Need to Talk! - Fundamental Misconceptions in Current XAI Research. - Timo Freiesleben; Gunnar König (xAI (1), 2023)

Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process. - Christoph Molnar; Timo Freiesleben; Gunnar König; Julia Herbinger; Tim Reisinger; Giuseppe Casalicchio; Marvin N. Wright; Bernd Bischl (xAI (1), 2023)

If interpretability is the answer, what is the question?: a causal perspective. - Gunnar König (2023)

CountARFactuals - Generating Plausible Model-Agnostic Counterfactual Explanations with Adversarial Random Forests. - Susanne Dandl; Kristin Blesch; Timo Freiesleben; Gunnar König; Jan Kapar; Bernd Bischl; Marvin N. Wright (xAI (3), 2024)

A Guide to Feature Importance Methods for Scientific Inference. - Fiona Katharina Ewald; Ludwig Bothmann; Marvin N. Wright; Bernd Bischl; Giuseppe Casalicchio; Gunnar König (xAI (2), 2024)

Disentangling Interactions and Dependencies in Feature Attribution. - Gunnar König; Eric Günther; Ulrike von Luxburg (CoRR, 2024)

Model-agnostic feature importance and effects with dependent features: a conditional subgroup approach. - Christoph Molnar; Gunnar König; Bernd Bischl; Giuseppe Casalicchio (Data Min. Knowl. Discov., 2024)

Scientific Inference with Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena. - Timo Freiesleben; Gunnar König; Christoph Molnar; Álvaro Tejero-Cantero (Minds Mach., 2024)

Disentangling Interactions and Dependencies in Feature Attributions. - Gunnar König; Eric Günther; Ulrike von Luxburg (AISTATS, 2025)

Performative Validity of Recourse Explanations. - Gunnar König; Hidde Fokkema; Timo Freiesleben; Celestine Mendler-Dünner; Ulrike von Luxburg (CoRR, 2025)