Exploiting tree-based variable importances to selectively identify relevant variables. - Vân Anh Huynh-Thu; Louis Wehenkel; Pierre Geurts (FSDM, 2008)

Statistical interpretation of machine learning-based feature importance scores for biomarker discovery. - Vân Anh Huynh-Thu; Yvan Saeys; Louis Wehenkel; Pierre Geurts (Bioinform., 2012)

Machine learning-based feature ranking: Statistical interpretation and gene network inference. - Vân Anh Huynh-Thu (2012)

Combining tree-based and dynamical systems for the inference of gene regulatory networks. - Vân Anh Huynh-Thu; Guido Sanguinetti (Bioinform., 2015)

Context-dependent feature analysis with random forests. - Antonio Sutera; Gilles Louppe; Vân Anh Huynh-Thu; Louis Wehenkel; Pierre Geurts (UAI, 2016)

Nets Versus Trees for Feature Ranking and Gene Network Inference. - Nicolas Vecoven; Jean-Michel Begon; Antonio Sutera; Pierre Geurts; Vân Anh Huynh-Thu (DS, 2020)

From global to local MDI variable importances for random forests and when they are Shapley values. - Antonio Sutera; Gilles Louppe; Vân Anh Huynh-Thu; Louis Wehenkel; Pierre Geurts (NeurIPS, 2021)

Knowledge-Guided Additive Modeling for Supervised Regression. - Yann Claes; Vân Anh Huynh-Thu; Pierre Geurts (DS, 2023)

Optimizing model-agnostic random subspace ensembles. - Vân Anh Huynh-Thu; Pierre Geurts (Mach. Learn., 2024)

Hybrid additive modeling with partial dependence for supervised regression and dynamical systems forecasting. - Yann Claes; Vân Anh Huynh-Thu; Pierre Geurts (Mach. Learn., 2025)