17 citations · 20 across the 6 of their papers we have counts for
6 papers
Independent Component Analysis by Robust Distance Correlation
Sarah Leyder, Jakob Raymaekers, Peter J. Rousseeuw +2
Independent component analysis (ICA) is a powerful tool for decomposing a multivariate signal or distribution into fully independent sources, not just uncorrelated ones. Unfortunat…
A Powerful Random Forest Featuring Linear Extensions (RaFFLE)
Jakob Raymaekers, Peter J. Rousseeuw, Thomas Servotte +2
Random forests are widely used in regression. However, the decision trees used as base learners are poor approximators of linear relationships. To address this limitation we propos…
RobPy: a Python Package for Robust Statistical Methods
Sarah Leyder, Jakob Raymaekers, Peter J. Rousseeuw +2
Robust estimation provides essential tools for analyzing data that contain outliers, ensuring that statistical models remain reliable even in the presence of some anomalous data. W…
TSLiNGAM: DirectLiNGAM under heavy tails
Sarah Leyder, Jakob Raymaekers, Tim Verdonck
One of the established approaches to causal discovery consists of combining directed acyclic graphs (DAGs) with structural causal models (SCMs) to describe the functional dependenc…
Generalized Spherical Principal Component Analysis
Sarah Leyder, Jakob Raymaekers, Tim Verdonck
Outliers contaminating data sets are a challenge to statistical estimators. Even a small fraction of outlying observations can heavily influence most classical statistical methods.…
Fast Linear Model Trees by PILOT
Jakob Raymaekers, Peter J. Rousseeuw, Tim Verdonck +1
Linear model trees are regression trees that incorporate linear models in the leaf nodes. This preserves the intuitive interpretation of decision trees and at the same time enables…