Do little interactions get lost in dark random forests? - Marvin N. Wright; Andreas Ziegler 001; Inke R. König (BMC Bioinform., 2016)

Random forests for survival analysis using maximally selected rank statistics. - Marvin N. Wright; Theresa Dankowski; Andreas Ziegler 001 (CoRR, 2016)

On the use of Harrell's C for clinical risk prediction via random survival forests. - Matthias Schmid; Marvin N. Wright; Andreas Ziegler 001 (Expert Syst. Appl., 2016)

The revival of the Gini importance? - Stefano Nembrini; Inke R. König; Marvin N. Wright (Bioinform., 2018)

Support Vector Machines for Survival Analysis with R. - Césaire J. K. Fouodo; Inke R. König; Claus Weihs; Andreas Ziegler 001; Marvin N. Wright (R J., 2018)

Block Forests: random forests for blocks of clinical and omics covariate data. - Roman Hornung; Marvin N. Wright (BMC Bioinform., 2019)

Testing Conditional Predictive Independence in Supervised Learning Algorithms. - David S. Watson; Marvin N. Wright (CoRR, 2019)

Hyperparameters and tuning strategies for random forest. - Philipp Probst; Marvin N. Wright; Anne-Laure Boulesteix (WIREs Data Mining Knowl. Discov., 2019)

Discrete-time survival forests with Hellinger distance decision trees. - Matthias Schmid; Thomas Welchowski; Marvin N. Wright; Moritz Berger (Data Min. Knowl. Discov., 2020)

Generalization of the Change of Variables Formula with Applications to Residual Flows. - Niklas Koenen; Marvin N. Wright; Peter Maaß; Jens Behrmann (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)

Testing conditional independence in supervised learning algorithms. - David S. Watson; Marvin N. Wright (Mach. Learn., 2021)

Are SHAP Values Biased Towards High-Entropy Features? - Raphael Baudeu; Marvin N. Wright; Markus Loecher (PKDD/ECML Workshops (1), 2022)

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)

Unifying local and global model explanations by functional decomposition of low dimensional structures. - Munir Hiabu; Joseph T. Meyer; Marvin N. Wright (AISTATS, 2023)

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)

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)

arfpy: A python package for density estimation and generative modeling with adversarial random forests. - Kristin Blesch; Marvin N. Wright (CoRR, 2023)

survex: an R package for explaining machine learning survival models. - Mikolaj Spytek; Mateusz Krzyzinski; Sophie Hanna Langbein; Hubert Baniecki; Marvin N. Wright; Przemyslaw Biecek (Bioinform., 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)

Toward Understanding the Disagreement Problem in Neural Network Feature Attribution. - Niklas Koenen; Marvin N. Wright (xAI (3), 2024)

Interpretable Machine Learning for Survival Analysis. - Sophie Hanna Langbein; Mateusz Krzyzinski; Mikolaj Spytek; Hubert Baniecki; Przemyslaw Biecek; Marvin N. Wright (CoRR, 2024)

A Large-Scale Neutral Comparison Study of Survival Models on Low-Dimensional Data. - Lukas Burk; John Zobolas; Bernd Bischl; Andreas Bender 001; Marvin N. Wright; Raphael Sonabend (CoRR, 2024)

Fast Estimation of Partial Dependence Functions using Trees. - Jinyang Liu; Tessa Steensgaard; Marvin N. Wright; Niklas Pfister; Munir Hiabu (CoRR, 2024)

Interpreting Deep Neural Networks with the Package innsight. - Niklas Koenen; Marvin N. Wright (J. Stat. Softw., 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)

Gradient-based Explanations for Deep Learning Survival Models. - Sophie Hanna Langbein; Niklas Koenen; Marvin N. Wright (CoRR, 2025)

Autoencoding Random Forests. - Binh Duc Vu; Jan Kapar; Marvin N. Wright; David S. Watson (CoRR, 2025)

Missing value imputation with adversarial random forests - MissARF. - Pegah Golchian; Jan Kapar; David S. Watson; Marvin N. Wright (CoRR, 2025)