2023 // book-chapter
Are SHAP Values Biased Towards High-Entropy Features?
Raphael Baudeu; Marvin N. Wright; Markus Loecher
2023 // conference-paper
Adversarial Random Forests for Density Estimation and Generative Modeling
Proceedings of The 26th International Conference on Artificial Intelligence and Statistics
Watson, David S.; Blesch, Kristin; Kapar, Jan; Wright, Marvin N.; Ruiz, Francisco; Dy, Jennifer; van de Meent, Jan-Willem
DOI: 10.48550/arXiv.2205.09435
2023 // conference-paper
Unifying local and global model explanations by functional decomposition of low dimensional structures
Proceedings of The 26th International Conference on Artificial Intelligence and Statistics
Hiabu, Munir; Meyer, Joseph T.; Wright, Marvin N.; Ruiz, Francisco; Dy, Jennifer; van de Meent, Jan-Willem
DOI: 10.48550/arXiv.2208.06151
2023 // journal-article
Conditional feature importance for mixed data
AStA Advances in Statistical Analysis
Blesch, K.; Watson, D.S.; Wright, M.N.
DOI: 10.1007/s10182-023-00477-9
Jan 2022 // preprint
Forest tree species distribution for Europe 2000-2020: mapping potential and realized distributions using spatiotemporal Machine Learning
Carmelo Bonannella; Tomislav Hengl; Johannes Heisig; Leandro Parente; Marvin N Wright; Martin Herold; Sytze de Bruin
2022 // journal-article
Special issue: Artificial intelligence in genomics
Human Genetics
Boulesteix, A.-L.; Wright, M.
DOI: 10.1007/s00439-022-02472-7
2022 // other
A Discovery and Verification Approach for Pharmacovigilance using Electronic Health Care Data
medRxiv
Dijkstra, L.J.; Schink, T.; Linder, R.; Schwaninger, M.; Pigeot, I.; Wright, M.N.; Foraita, R.
DOI: 10.1101/2022.05.10.22274885
2021 // other
Generalization of the change of variables formula with applications to residual flows
arXiv
Koenen, N.; Wright, M.N.; Maaß, P.; Behrmann, J.
DOI:
2021 // journal-article
Personalised need of care in an ageing society: The making of a prediction tool based on register data
Journal of the Royal Statistical Society. Series A: Statistics in Society
Wright, M.N.; Kusumastuti, S.; Mortensen, L.H.; Westendorp, R.G.J.; Gerds, T.A.
DOI: 10.1111/rssa.12644
2021 // other
Relating the partial dependence plot and permutation feature importance to the data generating process
arXiv
Molnar, C.; Freiesleben, T.; König, G.; Casalicchio, G.; Wright, M.N.; Bischl, B.
DOI:
2021 // journal-article
Polygenic risk for obesity and its interaction with lifestyle and sociodemographic factors in European children and adolescents
International Journal of Obesity
Hüls, A.; Wright, M.N.; Bogl, L.H.; Kaprio, J.; Lissner, L.; Molnár, D.; Moreno, L.A.; De Henauw, S.; Siani, A.; Veidebaum, T.; Ahrens, W.; Pigeot, I.; Foraita, R.
DOI: 10.1038/s41366-021-00795-5
2021 // journal-article
Testing conditional independence in supervised learning algorithms
Machine Learning
Watson, D.S.; Wright, M.N.
DOI: 10.1007/s10994-021-06030-6
2021 // journal-article
Association of Individual Motor Abilities and Accelerometer-Derived Physical Activity Measures in Preschool-Aged Children
Journal for the Measurement of Physical Behaviour
Breau, B.; Brandes, B.; Wright, M.N.; Buck, C.; Vallis, L.A.; Brandes, M.
DOI: 10.1123/jmpb.2020-0065
2021 // journal-article
The Translational Machine: A novel machine-learning approach to illuminate complex genetic architectures
Genetic Epidemiology
Askland, K.D.; Strong, D.; Wright, M.N.; Moore, J.H.
DOI: 10.1002/gepi.22383
2020 // journal-article
Impact of “JolinchenKids-Fit and healthy in Daycare” on children's objectively measured physical activity: A cluster-controlled study
Journal of Physical Activity and Health
Brandes, B.; Buck, C.; Wright, M.N.; Pischke, C.R.; Brandes, M.
DOI: 10.1123/jpah.2019-0536
2020 // other
A healthy childhood environment helps to combat inherited susceptibility to obesity
bioRxiv
Hüls, A.; Wright, M.N.; Bogl, L.H.; Kaprio, J.; Lissner, L.; Molnár, D.; Moreno, L.; De Henauw, S.; Siani, A.; Veidebaum, T.; Ahrens, W.; Pigeot, I.; Foraita, R.
DOI: 10.1101/2020.01.13.905125
2020 // journal-article
Discrete-time survival forests with Hellinger distance decision trees
Data Mining and Knowledge Discovery
Schmid, M.; Welchowski, T.; Wright, M.N.; Berger, M.
DOI: 10.1007/s10618-020-00682-z
2020 // journal-article
Statistical learning approaches in the genetic epidemiology of complex diseases
Human genetics
DOI: 10.1007/s00439-019-01996-9
2020 // journal-article
Erratum: Impact of “JolinchenKids—Fit and healthy in Daycare” on children’s objectively measured physical activity: A cluster-controlled study (Journal of Physical Activity and Health (2020) 17:10 (1025-1033) DOI: 10.1123/jpah.2019-0536)
Journal of Physical Activity and Health
Brandes, B.; Buck, C.; Wright, M.N.; Pischke, C.R.; Brandes, M.
DOI: 10.1123/jpah.2020-0647
2019 // journal-article
A Random Forest Approach for Bounded Outcome Variables
Journal of Computational and Graphical Statistics
DOI: 10.1080/10618600.2019.1705310
2019 // journal-article
Accelerometry-Based Prediction of Energy Expenditure in Preschoolers
Journal for the Measurement of Physical Behaviour
DOI:
2019 // journal-article
Block Forests: random forests for blocks of clinical and omics covariate data
BMC bioinformatics
DOI: 10.1186/s12859-019-2942-y
2019 // journal-article
Hyperparameters and tuning strategies for random forest
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
DOI: 10.1002/widm.1301
2019 // journal-article
Splitting on categorical predictors in random forests
PeerJ
2018 // journal-article
Support Vector Machines for Survival Analysis with R.
R Journal
DOI: 10.32614/rj-2018-005
