Sven Serneels

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Christophe CrouxKU Leuven - Faculty of Economics and BusinessPatvirtintas el. paštas kuleuven.be
Tim VerdonckProfessor Statistics and Data Science, UAntwerpPatvirtintas el. paštas uantwerpen.be
Peter FilzmoserProfessor of Statistics, TU WienPatvirtintas el. paštas tuwien.ac.at
Beata WalczakInstitute of Chemistry, University of Silesia in KatowicePatvirtintas el. paštas us.edu.pl
Michal DaszykowskiProfessor in chemometrics, Institute of Chemistry, University of Silesia in Katowice, PolandPatvirtintas el. paštas us.edu.pl
Emmanuel Jordy MenvoutaPhD researcher, KU LeuvenPatvirtintas el. paštas dataroots.io
Michiel DebruyneCredit Risk Modeling, DexiaPatvirtintas el. paštas dexia.com
Jason B. ChoCornell UniversityPatvirtintas el. paštas cornell.edu
David S. MattesonProfessor, Statistics & Data Science, Cornell UniversityPatvirtintas el. paštas cornell.edu
Ricardo Antonio MaronnaProfesor Consulto de la Facultad de Ciencias Exactas, Universidad Nacional de La PlataPatvirtintas el. paštas mate.unlp.edu.ar
Frank BlockhuysStructural Chemistry Group, University of AntwerpPatvirtintas el. paštas uantwerpen.be
Ivana StanimirovaUniversity of Silesia in Katowice, Institute of chemistryPatvirtintas el. paštas us.edu.pl
Arijit ChakrabortyPh.D. Student at the Department of Chemical Engineering, Columbia University in the City of New YorkPatvirtintas el. paštas columbia.edu
Venkat VenkatasubramanianSamuel Ruben-Peter G. Viele Professor of Engineering, Columbia UniversityPatvirtintas el. paštas columbia.edu
Pieter SegaertUniversity of AntwerpPatvirtintas el. paštas telenet.be

Stebėti

Sven Serneels

Technology Director - Data Science, Aspen Technology

Patvirtintas el. paštas aspentech.com

Big Data Analytics Chemometrics Quantitative Finance Machine Learning Time Series Analysis


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Partial robust M-regression S Serneels, C Croux, P Filzmoser, PJ Van Espen Chemometrics and Intelligent Laboratory Systems 79 (1-2), 55-64, 2005	246	2005
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	240	2007
Principal component analysis for data containing outliers and missing elements S Serneels, T Verdonck Computational Statistics & Data Analysis 52 (3), 1712-1727, 2008	188	2008
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	75	2006
Robust continuum regression S Serneels, P Filzmoser, C Croux, PJ Van Espen Chemometrics and Intelligent Laboratory Systems 76 (2), 197-204, 2005	55	2005
Sparse partial robust M regression I Hoffmann, S Serneels, P Filzmoser, C Croux Chemometrics and Intelligent Laboratory Systems 149, 50-59, 2015	54	2015
Robust multivariate methods in chemometrics P Filzmoser, S Serneels, R Maronna, C Croux Comprehensive Chemometrics, 2nd Edition, Steven Brown, Roma Tauler and Beata …, 2020	49	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	39	2004
Sparse and robust PLS for binary classification I Hoffmann, P Filzmoser, S Serneels, K Varmuza Journal of Chemometrics 30, 153-162, 2016	35	2016
Principal component regression for data containing outliers and missing elements S Serneels, T Verdonck Computational statistics & data analysis 53 (11), 3855-3863, 2009	34	2009
Detecting wash trading for nonfungible tokens S Serneels Finance Research Letters 52, 103374, 2023	33	2023
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	29	2007
Influence properties of partial least squares regression S Serneels, C Croux, PJ Van Espen Chemometrics and Intelligent Laboratory Systems 71 (1), 13-20, 2004	28	2004
Cellwise robust M regression P Filzmoser, S Höppner, I Ortner, S Serneels, T Verdonck Computational Statistics & Data Analysis 147, 106944, 2020	26	2020
Non-fungible token transactions: data and challenges JB Cho, S Serneels, DS Matteson Data Science in Science 2 (1), 2151950, 2023	24	2023
Outlyingness: which variables contribute most? M Debruyne, S Höppner, S Serneels, T Verdonck Statistics and Computing 29, 707-723, 2019	22	2019
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	19	2006
Bootstrap confidence intervals for trilinear partial least squares regression S Serneels, PJ Van Espen Analytica chimica acta 544 (1-2), 153-158, 2005	19	2005
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
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	12	2004

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