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@VerbekeLab

VerbekeLab

Advancing the science and practice of data-driven decision-making
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Verbeke Lab

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Research Topics

TopicAcronym
Causal Machine LearningCML
Machine Learning for Decision-MakingMLDM
Cost-Sensitive LearningCSL
Credit Risk ManagementCRM
Fraud Risk ManagementFRM

Research

YearFirst AuthorPaperCodeVenueTopic
2026Rickermann C.A Data-Centric Decomposition of Estimator Performance in Continuous Treatment Effect EstimationCodeCML
Vandervorst F.Inductive inference of gradient-boosted decision trees on graphs for insurance fraud detectionCodeData Mining and Knowledge DiscoveryFRM
2025Deprez B.Network Analytics for Anti-money Laundering—A Systematic Literature Review and Experimental EvaluationCodeINFORMS Journal on Data ScienceFRM
De Vos S.Uplift modeling with continuous treatments: a predict-then-optimize approachCodeEuropean Journal of Operational ResearchCML
Caljon D.Optimizing Treatment Allocation in the Presence of InterferenceCodeEuropean Journal of Operational ResearchCML
Vanderschueren T.AutoCATE: End-to-End, Automated Treatment Effect EstimationCodeProceedings of Machine Learning ResearchCML
Deprez B.Advances in Continual Graph Learning for Anti-Money Laundering Systems: A Comprehensive ReviewCodeWIREs Computational Statistics JournalFRM
Caljon D.Using adaptive loss balancing to boost improvements in forecast stabilityCodeInternational Journal of ForecastingMLDM
Rickermann C.Using representation balancing to learn conditional-average dose responses from clustered dataCodeTransactions on Machine Learning ResearchCML
Verbeken B.Uplift Model Evaluation with Ordinal Dominance GraphsCodeJournal of Machine Learning ResearchCML
Rickermann C.Can causal machine learning reveal individual bid responses of bank customers? — A study on mortgage loan applications in BelgiumCodeDecision Support SystemsCML
2024Van Belle J.Probabilistic forecasting with modified N-BEATS networks CodeIEEE Transactions on Neural Learning SystemsMLDM
De Vos S.Predicting Employee Turnover: Scoping and Benchmarking the State-of-the-ArtCodeBusiness Information Systems EngineeringMLDM
Reusens M.A review and experimental evaluation of the state-of-the-art in text classificationCode Expert Systems with ApplicationsMLDM
Deprez B.Network analytics for insurance fraud detection: a critical case studyCodeEuropean Actuarial JournalFRM
De Vos S.Data-driven internal mobility: getting the job done with similarity regularizationCodeKnowledge Based SystemsMLDM
Vanderschueren T.A new perspective on classification: Optimally allocating limited resources to uncertain tasksCodeDecision Support SystemsCSL
2023Weytjens H.Timed Process Interventions: Causal Inference vs. Reinforcement LearningCodeLecture Notes in Business Information ProcessingCML
Vanderschueren T.Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over TimeCodeInternational Conference on Machine LearningCML
Scheltjens V.Client Recruitment for Federated Learning in ICU Length of Stay PredictionCodeInternational Conference on e-ScienceMLDM
Vanderschueren T.NOFLITE: Learning to Predict Individual Treatment Effect DistributionsCodeTransactions on Machine Learning ResearchCML
De Bock K.Explainable Analytics in Operational Research: Methods, Applications and an Agenda for Future ResearchEuropean Journal of Operational ResearchMLDM
Vanderschueren T.A new perspective on classification: Optimally allocating limited resources to uncertain tasksCodeDecision Support SystemsCSL
Vandervorst F.Claims fraud detection with uncertain labelsAdvances in Data Analysis and ClassificationFRM
Rickermann C.A decade of research on fraud analytics: challenges and methodsDataExpert Systems with ApplicationsFRM
De Vos S.Robust instance-dependent cost-sensitive classificationCodeAdvances in Data Analysis and ClassificationCSL
Van Belle J.Improving forecast stability using deep learningCodeInternational Journal of ForecastingMLDM
Vanderschueren T.Optimizing the preventive maintenance frequency with causal machine learningCodeInternational Journal of Production EconomicsCML
Verbeke W.To do or not to do: Cost-sensitive causal decision-makingCodeEuropean Journal of Operational ResearchCML
2022Coenen L.Machine learning methods for short-term Probability of Default A comparison of classification, regression and ranking methodsJournal of the Operational Research SocietyFRM
Verboven S.HydaLearn: Highly Dynamic Task Weighting for Multi-task Learning with Auxiliary TasksCodeApplied IntelligenceMLDM
Berrevoets J.Individual treatment effect optimisation in dynamic environmentsCodeJournal of Causal InferenceCML
Devriendt F.Learning 2 Rank for uplift modelingIEEE Transactions on Knowledge and Data EngineeringCML
Vandervorst F.Data misrepresentation detection for insurance underwriting fraud preventionDecision Support SystemsFRM
Petrides G.Cost-sensitive learning for profit-driven credit scoringDataJournal of the Operational Research SocietyCSL
Vanderschueren T.Predict-then-optimize or predict-and-optimize? An empirical evaluation of cost-sensitive learning strategiesCodeInformation SystemsCSL FRM
Petrides G.Cost-sensitive ensemble learning: a unifying frameworkData Mining and Knowledge DiscoveryCSL
Hoppner S.Instance-Dependent Cost-Sensitive Learning for Detecting Transfer Fraud Using Lasso-Regularized Logistic Regression and Gradient Boosted Decision TreesCodeEuropean Journal of Operational ResearchCSL
Raymaekers J.Weight-of-evidence through shrinkage and spline binning for interpretable nonlinear classificationCodeApplied Soft ComputingFRM CRM
2021De Caigny A.Uplift modeling and its implications for B2B customer churn prediction: A segmentation-based modeling approachIndustrial Marketing ManagementCML
Siozos-Rousoulis L.A study of the U.S. domestic air transportation network: Temporal evolution of network topology and robustness from 2001 to 2016CodeJournal of Transportation Safety and SecurityMLDM
Maldonado S.Profit-driven Churn Prediction for the Mutual Fund Industry: a Multi-segment ApproachOmegaCSL
Maldonado S.Redefining Profit Metrics for boosting Student Retention in Higher EducationDecision Support SystemsCSL
Devriendt F.Why you should stop predicting customer churn and start using uplift modelingCodeInformation SciencesCML CSL
Van Belle J.Using shared sell-through data to forecast wholesaler demand in multi-echelon supply chainsEuropean Journal of Operational ResearchMLDM
2020Verboven S.Auto-encoders for strategic decision supportDecision Support SystemsMLDM
Olaya D.Uplift Modeling for Preventing Student Dropout in Higher EducationCodeDecision Support SystemsCML
Benoit D.Article Commentary: On realizing the utopian potential of big data analytics for maximizing return on marketing investmentsJournal of Marketing ManagementCSL
Olaya D.A survey and benchmarking study of multitreatment uplift modelingCodeData Mining and Knowledge DiscoveryCML
Decauwer C.A Model for Range Estimation and Energy-Efficient Routing of Electric Vehicles in Real-world ConditionsIEEE Transactions on Intelligent Transportation SystemsMLDM

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