Robust Multivariate Methods: The Projection Pursuit Approach. - Peter Filzmoser; Sven Serneels; Christophe Croux; Pierre J. Van Espen (GfKl, 2005)

The Partial Robust M-approach. - Sven Serneels; Christophe Croux; Peter Filzmoser; Pierre J. Van Espen (GfKl, 2005)

Spatial Sign Preprocessing: A Simple Way To Impart Moderate Robustness to Multivariate Estimators. - Sven Serneels; Evert De Nolf; Pierre J. Van Espen (J. Chem. Inf. Model., 2006)

Principal component analysis for data containing outliers and missing elements. - Sven Serneels; Tim Verdonck (Comput. Stat. Data Anal., 2008)

Principal component regression for data containing outliers and missing elements. - Sven Serneels; Tim Verdonck (Comput. Stat. Data Anal., 2009)

Outlyingness: Which variables contribute most? - Michiel Debruyne; Sebastiaan Höppner; Sven Serneels; Tim Verdonck (Stat. Comput., 2019)

Cellwise robust M regression. - Peter Filzmoser; Sebastiaan Höppner; Irene Ortner; Sven Serneels; Tim Verdonck (Comput. Stat. Data Anal., 2020)

Sparse dimension reduction based on energy and ball statistics. - Emmanuel Jordy Menvouta; Sven Serneels; Tim Verdonck (Adv. Data Anal. Classif., 2022)

direpack: A Python 3 package for state-of-the-art statistical dimensionality reduction methods. - Emmanuel Jordy Menvouta; Sven Serneels; Tim Verdonck (SoftwareX, 2023)