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Sven Serneels
Sven Serneels
Technology Director - Data Science, Aspen Technology
Verified email at aspentech.com
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Cited by
Cited by
Year
TOMCAT: A MATLAB toolbox for multivariate calibration techniques
M Daszykowski, S Serneels, K Kaczmarek, P Van Espen, C Croux, ...
Chemometrics and intelligent laboratory systems 85 (2), 269-277, 2007
2352007
Partial robust M-regression
S Serneels, C Croux, P Filzmoser, PJ Van Espen
Chemometrics and Intelligent Laboratory Systems 79 (1-2), 55-64, 2005
2352005
Principal component analysis for data containing outliers and missing elements
S Serneels, T Verdonck
Computational Statistics & Data Analysis 52 (3), 1712-1727, 2008
1772008
Spatial sign preprocessing: a simple way to impart moderate robustness to multivariate estimators
S Serneels, E De Nolf, PJ Van Espen
Journal of Chemical Information and Modeling 46 (3), 1402-1409, 2006
692006
Robust continuum regression
S Serneels, P Filzmoser, C Croux, PJ Van Espen
Chemometrics and Intelligent Laboratory Systems 76 (2), 197-204, 2005
542005
Sparse partial robust M regression
I Hoffmann, S Serneels, P Filzmoser, C Croux
Chemometrics and Intelligent Laboratory Systems 149, 50-59, 2015
512015
Robust multivariate methods in chemometrics
P Filzmoser, S Serneels, R Maronna, C Croux
Comprehensive Chemometrics, 2nd Edition, Steven Brown, Roma Tauler and Beata …, 2020
44*2020
Calculation of PLS prediction intervals using efficient recursive relations for the Jacobian matrix
S Serneels, P Lemberge, PJ Van Espen
Journal of Chemometrics: A Journal of the Chemometrics Society 18 (2), 76-80, 2004
372004
Sparse and robust PLS for binary classification
I Hoffmann, P Filzmoser, S Serneels, K Varmuza
Journal of Chemometrics 30, 153-162, 2016
332016
Principal component regression for data containing outliers and missing elements
S Serneels, T Verdonck
Computational statistics & data analysis 53 (11), 3855-3863, 2009
322009
Detecting wash trading for nonfungible tokens
S Serneels
Finance Research Letters 52, 103374, 2023
272023
How to construct a multiple regression model for data with missing elements and outlying objects
I Stanimirova, S Serneels, PJ Van Espen, B Walczak
Analytica chimica acta 581 (2), 324-332, 2007
272007
Influence properties of partial least squares regression
S Serneels, C Croux, PJ Van Espen
Chemometrics and Intelligent Laboratory Systems 71 (1), 13-20, 2004
262004
Cellwise robust M regression
P Filzmoser, S Höppner, I Ortner, S Serneels, T Verdonck
Computational Statistics & Data Analysis 147, 106944, 2020
222020
Robust multivariate methods: The projection pursuit approach
P Filzmoser, S Serneels, C Croux, PJ Van Espen
From Data and Information Analysis to Knowledge Engineering: Proceedings of …, 2006
192006
Outlyingness: Which variables contribute most?
M Debruyne, S Höppner, S Serneels, T Verdonck
Statistics and Computing 29, 707-723, 2019
182019
Bootstrap confidence intervals for trilinear partial least squares regression
S Serneels, PJ Van Espen
Analytica chimica acta 544 (1-2), 153-158, 2005
182005
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
142009
Non-fungible token transactions: data and challenges
JB Cho, S Serneels, DS Matteson
Data Science in Science 2 (1), 2151950, 2023
132023
Identification of micro-organisms by dint of the electronic nose and trilinear partial least squares regression
S Serneels, M Moens, PJ Van Espen, F Blockhuys
Analytica chimica acta 516 (1-2), 1-5, 2004
122004
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