Smooth densities and generative modeling with unsupervised random forests. - David S. Watson; Kristin Blesch; Jan Kapar; Marvin N. Wright (CoRR, 2022)

Conditional Feature Importance for Mixed Data. - Kristin Blesch; David S. Watson; Marvin N. Wright (CoRR, 2022)

Adversarial Random Forests for Density Estimation and Generative Modeling. - David S. Watson; Kristin Blesch; Jan Kapar; Marvin N. Wright (AISTATS, 2023)

Unfooling SHAP and SAGE: Knockoff Imputation for Shapley Values. - Kristin Blesch; Marvin N. Wright; David S. Watson (xAI (1), 2023)

arfpy: A python package for density estimation and generative modeling with adversarial random forests. - Kristin Blesch; Marvin N. Wright (CoRR, 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)

Interpretable machine learning and generative modeling with mixed tabular data - advancing methodology from the perspective of statistics - Kristin Blesch (2024)

Conditional Feature Importance with Generative Modeling Using Adversarial Random Forests. - Kristin Blesch; Niklas Koenen; Jan Kapar; Pegah Golchian; Lukas Burk; Markus Loecher; Marvin N. Wright (AAAI, 2025)