Tom F. Wilderjans

SymBioSys Katholieke Universiteit Leuven, Leuven, Vlaanderen, Belgium 
"Tom Wilderjans"
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Cariou V, Alexandre‐Gouabau M, Wilderjans TF. (2020) Three‐way clustering around latent variables approach with constraints on the configurations to facilitate interpretation Journal of Chemometrics
Durieux J, Wilderjans TF. (2019) Partitioning subjects based on high-dimensional fMRI data: comparison of several clustering methods and studying the influence of ICA data reduction in big data Behaviormetrika. 46: 271-311
Waaijenborg S, Korobko O, Dijk KWv, et al. (2018) Fusing metabolomics data sets with heterogeneous measurement errors Plos One. 13
Cariou V, Wilderjans TF. (2017) Consumer segmentation in multi-attribute product evaluation by means of non-negatively constrained CLV3W Food Quality and Preference. 67: 18-26
Doove LL, Wilderjans TF, Calcagnì A, et al. (2017) Deriving optimal data-analytic regimes from benchmarking studies Computational Statistics & Data Analysis. 107: 81-91
Wilderjans TF, Vande Gaer E, Kiers HA, et al. (2016) Principal Covariates Clusterwise Regression (PCCR): Accounting for Multicollinearity and Population Heterogeneity in Hierarchically Organized Data. Psychometrika
Ceulemans E, Wilderjans TF, Kiers HA, et al. (2015) MultiLevel simultaneous component analysis: A computational shortcut and software package. Behavior Research Methods
Schouteden M, Van Deun K, Wilderjans TF, et al. (2014) Performing DISCO-SCA to search for distinctive and common information in linked data. Behavior Research Methods. 46: 576-87
Wilderjans TF, Cariou V. (2014) CLV3W: A clustering around latent variables approach to detect panel disagreement in three-way conventional sensory profiling data Food Quality and Preference
Rodríguez SD, Barletta DA, Wilderjans TF, et al. (2014) Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection Food Analytical Methods. 7: 2042-2050
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