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

Robust PCA for skewed data and its outlier map. - Mia Hubert; Peter J. Rousseeuw; Tim Verdonck (Comput. Stat. Data Anal., 2009)

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

DetMCD in a Calibration Framework. - Tim Verdonck; Mia Hubert; Peter J. Rousseeuw (COMPSTAT, 2010)

Robust kernel principal component analysis and classification. - Michiel Debruyne; Tim Verdonck (Adv. Data Anal. Classif., 2010)

Comparing Mining Algorithms for Predicting the Severity of a Reported Bug. - Ahmed Lamkanfi; Serge Demeyer; Quinten David Soetens; Tim Verdonck (CSMR, 2011)

Precision of power-law NHPP estimates for multiple systems with known failure rate scaling. - Jozef Van Dyck; Tim Verdonck (Reliab. Eng. Syst. Saf., 2014)

The DetS and DetMM estimators for multivariate location and scatter. - Mia Hubert; Peter J. Rousseeuw; Dina Vanpaemel; Tim Verdonck (Comput. Stat. Data Anal., 2015)

Sparse PCA for High-Dimensional Data With Outliers. - Mia Hubert; Tom Reynkens; Eric Schmitt; Tim Verdonck (Technometrics, 2016)

Fast robust SUR with economical and actuarial applications. - Mia Hubert; Tim Verdonck; Özlem Yorulmaz (Stat. Anal. Data Min., 2017)

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

A Machine Learning Approach for Road Cycling Race Performance Prediction. - Leonid Kholkine; Tom De Schepper; Tim Verdonck; Steven Latré (MLSA@PKDD/ECML, 2020)

robROSE: A robust approach for dealing with imbalanced data in fraud detection. - Bart Baesens; Sebastiaan Höppner; Irene Ortner; Tim Verdonck (CoRR, 2020)

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

Profit driven decision trees for churn prediction. - Sebastiaan Höppner; Eugen Stripling; Bart Baesens; Seppe vanden Broucke; Tim Verdonck (Eur. J. Oper. Res., 2020)

The minimum regularized covariance determinant estimator. - Kris Boudt; Peter J. Rousseeuw; Steven Vanduffel; Tim Verdonck (Stat. Comput., 2020)

Weight-of-evidence 2.0 with shrinkage and spline-binning. - Jakob Raymaekers; Wouter Verbeke; Tim Verdonck (CoRR, 2021)

Data engineering for fraud detection. - Bart Baesens; Sebastiaan Höppner; Tim Verdonck (Decis. Support Syst., 2021)

Instance-dependent cost-sensitive learning: do we really need it? - Toon Vanderschueren; Wouter Verbeke; Bart Baesens; Tim Verdonck (HICSS, 2022)

Introduction to the Minitrack on Fraud Detection Using Machine Learning. - Tim Verdonck; Wouter Verbeke; Maria Óskarsdóttir; Bart Baesens (HICSS, 2022)

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

Weight-of-evidence through shrinkage and spline binning for interpretable nonlinear classification. - Jakob Raymaekers; Wouter Verbeke; Tim Verdonck (Appl. Soft Comput., 2022)

Prescriptive maintenance with causal machine learning. - Toon Vanderschueren; Robert N. Boute; Tim Verdonck; Bart Baesens; Wouter Verbeke (CoRR, 2022)

Data misrepresentation detection for insurance underwriting fraud prevention. - Félix Vandervorst; Wouter Verbeke; Tim Verdonck (Decis. Support Syst., 2022)

Instance-dependent cost-sensitive learning for detecting transfer fraud. - Sebastiaan Höppner; Bart Baesens; Wouter Verbeke; Tim Verdonck (Eur. J. Oper. Res., 2022)

Predict-then-optimize or predict-and-optimize? An empirical evaluation of cost-sensitive learning strategies. - Toon Vanderschueren; Tim Verdonck; Bart Baesens; Wouter Verbeke (Inf. Sci., 2022)

Oversampling Method Based Covariance Matrix Estimation in High-Dimensional Imbalanced Classification. - Ireimis Leguen-devarona; Julio Madera; Héctor R. Gonzalez; Lise Tubex; Tim Verdonck (IWAIPR, 2023)

A Causal Perspective on Loan Pricing: Investigating the Impacts of Selection Bias on Identifying Bid-Response Functions. - Christopher Bockel-Rickermann; Sam Verboven; Tim Verdonck; Wouter Verbeke (CoRR, 2023)

Learning continuous-valued treatment effects through representation balancing. - Christopher Bockel-Rickermann; Toon Vanderschueren; Jeroen Berrevoets; Tim Verdonck; Wouter Verbeke (CoRR, 2023)

Tree-based Forecasting of Day-ahead Solar Power Generation from Granular Meteorological Features. - Nick Berlanger; Noah van Ophoven; Tim Verdonck; Ines Wilms (CoRR, 2023)

Fast thresholded concordance probability for evolutionary optimization. - Jolien Ponnet; Jakob Raymaekers; Tim Verdonck (Swarm Evol. Comput., 2023)

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

Exploiting sensor data in professional road cycling: personalized data-driven approach for frequent fitness monitoring. - Arie-Willem de Leeuw; Mathieu Heijboer; Tim Verdonck; Arno J. Knobbe; Steven Latré (Data Min. Knowl. Discov., 2023)

Regularization oversampling for classification tasks: To exploit what you do not know. - Lennert Van der Schraelen; Kristof Stouthuysen; Seppe K. L. M. vanden Broucke; Tim Verdonck (Inf. Sci., 2023)

Robust instance-dependent cost-sensitive classification. - Simon De Vos; Toon Vanderschueren; Tim Verdonck; Wouter Verbeke (Adv. Data Anal. Classif., 2023)

Interpretable cost-sensitive regression through one-step boosting. - Thomas Decorte; Jakob Raymaekers; Tim Verdonck (Decis. Support Syst., 2023)

Fraud analytics: A decade of research: Organizing challenges and solutions in the field. - Christopher Bockel-Rickermann; Tim Verdonck; Wouter Verbeke (Expert Syst. Appl., 2023)

Smart initialisation and approximating loss function for robust regression. - Thomas Servotte; Jakob Raymaekers; Tim Verdonck (Inf. Sci., 2023)

Classification of Targets and Distractors in an Audiovisual Attention Task Based on Electroencephalography. - Steven Mortier; Renata Turkes; Jorg De Winne; Wannes Van Ransbeeck; Dick Botteldooren; Paul Devos; Steven Latré; Marc Leman; Tim Verdonck (Sensors, 2023)

Computational Efficient Approximations of the Concordance Probability in a Big Data Setting. - Robin Van Oirbeek; Jolien Ponnet; Bart Baesens; Tim Verdonck (Big Data, 2024)

Network Analytics for Anti-Money Laundering - A Systematic Literature Review and Experimental Evaluation. - Bruno Deprez; Toon Vanderschueren; Bart Baesens; Tim Verdonck; Wouter Verbeke (CoRR, 2024)

Sources of Gain: Decomposing Performance in Conditional Average Dose Response Estimation. - Christopher Bockel-Rickermann; Toon Vanderschueren; Tim Verdonck; Wouter Verbeke (CoRR, 2024)

Global Crop-Specific Fertilization Dataset from 1961-2019. - Fernando Coello; Thomas Decorte; Iris Janssens; Steven Mortier; Jordi Sardans; Josep Peñuelas; Tim Verdonck (CoRR, 2024)

A new perspective on classification: Optimally allocating limited resources to uncertain tasks. - Toon Vanderschueren; Bart Baesens; Tim Verdonck; Wouter Verbeke (Decis. Support Syst., 2024)

Inferring the relationship between soil temperature and the normalized difference vegetation index with machine learning. - Steven Mortier; Amir Hamedpour; Bart Bussmann; Ruth Phoebe Tchana Wandji; Steven Latré; Bjarni D. Sigurdsson; Tom De Schepper; Tim Verdonck (Ecol. Informatics, 2024)

Co-clustering contaminated data: a robust model-based approach. - Edoardo Fibbi; Domenico Perrotta; Francesca Torti; Stefan Van Aelst; Tim Verdonck (Adv. Data Anal. Classif., 2024)

Claims fraud detection with uncertain labels. - Félix Vandervorst; Wouter Verbeke; Tim Verdonck (Adv. Data Anal. Classif., 2024)

Missing Value Imputation of Wireless Sensor Data for Environmental Monitoring. - Thomas Decorte; Steven Mortier; Jonas J. Lembrechts; Filip J. R. Meysman; Steven Latré; Erik Mannens; Tim Verdonck (Sensors, 2024)

Generalized spherical principal component analysis. - Sarah Leyder; Jakob Raymaekers; Tim Verdonck (Stat. Comput., 2024)

Special issue on feature engineering editorial. - Tim Verdonck; Bart Baesens; María Óskarsdóttir; Seppe vanden Broucke (Mach. Learn., 2024)

Robust and sparse logistic regression. - Dries Cornilly; Lise Tubex; Stefan Van Aelst; Tim Verdonck (Adv. Data Anal. Classif., 2024)

Fast linear model trees by PILOT. - Jakob Raymaekers; Peter J. Rousseeuw; Tim Verdonck; Ruicong Yao (Mach. Learn., 2024)

Differentiable Causal Structure Learning with Identifiability by NOTIME. - Jeroen Berrevoets; Jakob Raymaekers; Mihaela van der Schaar; Tim Verdonck; Ruicong Yao (AISTATS, 2025)

Causal discovery in mixed additive noise models. - Ruicong Yao; Tim Verdonck; Jakob Raymaekers (AISTATS, 2025)

Can causal machine learning reveal individual bid responses of bank customers? - A study on mortgage loan applications in Belgium. - Christopher Bockel-Rickermann; Sam Verboven; Tim Verdonck; Wouter Verbeke (Decis. Support Syst., 2025)

Enhancing explainability in real-world scenarios: Towards a robust stability measure for local interpretability. - Eduardo Sepúlveda; Félix Vandervorst; Bart Baesens; Tim Verdonck (Expert Syst. Appl., 2025)

On the causality-preservation capabilities of generative modelling. - Yves-Cédric Bauwelinckx; Jan Dhaene; Milan van den Heuvel; Tim Verdonck (J. Comput. Appl. Math., 2025)

TSLiNGAM: DirectLiNGAM Under Heavy Tails. - Sarah Leyder; Jakob Raymaekers; Tim Verdonck (J. Comput. Graph. Stat., 2025)

Using representation balancing to learn conditional-average dose responses from clustered data. - Christopher Bockel-Rickermann; Toon Vanderschueren; Jeroen Berrevoets; Tim Verdonck; Wouter Verbeke (Trans. Mach. Learn. Res., 2025)

A Powerful Random Forest Featuring Linear Extensions (RaFFLE). - Jakob Raymaekers; Peter J. Rousseeuw; Thomas Servotte; Tim Verdonck; Ruicong Yao (CoRR, 2025)

Advances in Continual Graph Learning for Anti-Money Laundering Systems: A Comprehensive Review. - Bruno Deprez; Wei Wei; Wouter Verbeke; Bart Baesens; Kevin Mets; Tim Verdonck (CoRR, 2025)

Independent Component Analysis by Robust Distance Correlation. - Sarah Leyder; Jakob Raymaekers; Peter J. Rousseeuw; Tom Van Deuren; Tim Verdonck (CoRR, 2025)

GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money Laundering. - Bruno Deprez; Bart Baesens; Tim Verdonck; Wouter Verbeke (CoRR, 2025)