| Minimum covariance determinant M Hubert, M Debruyne Wiley interdisciplinary reviews: Computational statistics 2 (1), 36-43, 2010 | 331 | 2010 |
| Minimum covariance determinant and extensions M Hubert, M Debruyne, PJ Rousseeuw Wiley Interdisciplinary Reviews: Computational Statistics 10 (3), e1421, 2018 | 202 | 2018 |
| Robustness and outlier detection in chemometrics PJ Rousseeuw, M Debruyne, S Engelen, M Hubert Critical reviews in analytical chemistry 36 (3-4), 221-242, 2006 | 159 | 2006 |
| Model selection in kernel based regression using the influence function M Debruyne, M Hubert, JAK Suykens Journal of machine learning research.-Cambridge, Mass. 9, 2377-2400, 2008 | 103 | 2008 |
| Robustness of kernel based regression: a comparison of iterative weighting schemes K De Brabanter, K Pelckmans, J De Brabanter, M Debruyne, JAK Suykens, ... Artificial Neural Networks–ICANN 2009: 19th International Conference …, 2009 | 83 | 2009 |
| The incidence of multidrug and full class resistance in HIV-1 infected patients is decreasing over time (2001–2006) in Portugal J Vercauteren, K Deforche, K Theys, M Debruyne, LM Duque, S Peres, ... Retrovirology 5, 1-8, 2008 | 68 | 2008 |
| Robust kernel principal component analysis and classification M Debruyne, T Verdonck Advances in Data Analysis and Classification 4 (2), 151-167, 2010 | 59 | 2010 |
| Detecting influential observations in Kernel PCA M Debruyne, M Hubert, J Van Horebeek Computational Statistics & Data Analysis 54 (12), 3007-3019, 2010 | 40 | 2010 |
| An outlier map for support vector machine classification M Debruyne The Annals of Applied Statistics, 1566-1580, 2009 | 38 | 2009 |
| Breakdown value M Hubert, M Debruyne Wiley Interdisciplinary Reviews: Computational Statistics 1 (3), 296-302, 2009 | 37 | 2009 |
| The influence of individual claims on the chain-ladder estimates: Analysis and diagnostic tool T Verdonck, M Debruyne Insurance: Mathematics and Economics 48 (1), 85-98, 2011 | 34 | 2011 |
| Robustness of reweighted least squares kernel based regression M Debruyne, A Christmann, M Hubert, JAK Suykens Journal of Multivariate Analysis 101 (2), 447-463, 2010 | 33 | 2010 |
| The influence function of the Stahel–Donoho covariance estimator of smallest outlyingness M Debruyne, M Hubert Statistics & probability letters 79 (3), 275-282, 2009 | 27 | 2009 |
| Outlyingness: Which variables contribute most? M Debruyne, S Höppner, S Serneels, T Verdonck Statistics and Computing 29, 707-723, 2019 | 18 | 2019 |
| A proposed framework for backtesting loss given default models G Loterman, M Debruyne, K Vanden Branden, T Van Gestel, C Mues Journal of Risk Model Validation 8 (1), 69-90, 2014 | 16 | 2014 |
| Robustness and stability of reweighted kernel based regression M Debruyne, A Christmann, M Hubert, JAK Suykens Leuven, Belgium, 2008 | 16 | 2008 |
| Robustified least squares support vector classification M Debruyne, S Serneels, T Verdonck Journal of Chemometrics: A Journal of the Chemometrics Society 23 (9), 479-486, 2009 | 14 | 2009 |
| Censored depth quantiles M Debruyne, M Hubert, S Portnoy, KV Branden Computational statistics & data analysis 52 (3), 1604-1614, 2008 | 11 | 2008 |
| Robustness of censored depth quantiles, PCA and kernel based regression with new tools for model selection M Debruyne | 7 | 2007 |
| Wiley Interdiscip. Rev M Hubert, M Debruyne, PJ Rousseeuw Comput. Stat 10, e1421, 2018 | 4 | 2018 |
