Measuring inequality beyond the Gini coefficient may clarify conflicting findings K Blesch, OP Hauser, JM Jachimowicz Nature human behaviour 6 (11), 1525-1536, 2022 | 37 | 2022 |
Adversarial random forests for density estimation and generative modeling DS Watson, K Blesch, J Kapar, MN Wright International Conference on Artificial Intelligence and Statistics, 5357-5375, 2023 | 17* | 2023 |
Conditional feature importance for mixed data K Blesch, DS Watson, MN Wright AStA Advances in Statistical Analysis 108 (2), 259-278, 2024 | 10 | 2024 |
Unfooling SHAP and SAGE: knockoff imputation for Shapley values K Blesch, MN Wright, D Watson World Conference on Explainable Artificial Intelligence, 131-146, 2023 | 3 | 2023 |
arfpy: A Python Package for Density Estimation and Generative Modeling with Adversarial Random Forests K Blesch, MN Wright Journal of Open Research Software 12 (7), 2024 | 1 | 2024 |
MissARF: Adversarial random forests for imputing miss-ing values P Golchian, J Kapar, K Blesch, DS Watson, MN Wright Statistical Computing 2024, 13, 2024 | | 2024 |
Interpretable machine learning and generative modeling with mixed tabular data-advancing methodology from the perspective of statistics K Blesch Universität Bremen, 2024 | | 2024 |
CountARFactuals--Generating plausible model-agnostic counterfactual explanations with adversarial random forests S Dandl*, K Blesch*, T Freiesleben*, G König*, J Kapar, B Bischl, ... arXiv preprint arXiv:2404.03506, 2024 | | 2024 |