Wouter Verbeke

99 papers A* 2B 2Journal 86Unranked 6
YearRankTypeTitle / Venue / Authors
2026 J jnl
Optimizing treatment allocation in the presence of interference.
Eur. J. Oper. Res.
Daan Caljon, Jente Van Belle, Jeroen Berrevoets, Wouter Verbeke
2026 J jnl
Uplift modeling with continuous treatments: A predict-then-optimize approach.
Eur. J. Oper. Res.
Simon De Vos, Christopher Bockel-Rickermann, Stefan Lessmann, Wouter Verbeke
2025 J jnl
A prescriptive analytics framework for jointly optimizing retention incentives and targeting.
Knowl. Based Syst.
Paolo Latorre, Armando Meza, Héctor A. López-Ospina, Wouter Verbeke, Juan Pérez
2025 J jnl
Advances in Continual Graph Learning for Anti-Money Laundering Systems: A Comprehensive Review.
CoRR
Bruno Deprez, Wei Wei, Wouter Verbeke, Bart Baesens, Kevin Mets, Tim Verdonck
2025 A* conf
AutoCATE: End-to-End, Automated Treatment Effect Estimation.
ICML
Toon Vanderschueren, Tim Verdonck, Mihaela van der Schaar, Wouter Verbeke
2025 J jnl
Beware of "Explanations" of AI.
CoRR
David Martens, Galit Shmueli, Theodoros Evgeniou, Kevin Bauer, Christian Janiesch, Stefan Feuerriegel, Sebastian Gabel, Sofie Goethals, Travis Greene, Nadja Klein, Mathias Kraus, Niklas Kühl, Claudia Perlich, Wouter Verbeke, Alona Zharova, Patrick Zschech, Foster J. Provost
2025 J jnl
Can causal machine learning reveal individual bid responses of bank customers? - A study on mortgage loan applications in Belgium.
Decis. Support Syst.
Christopher Bockel-Rickermann, Sam Verboven, Tim Verdonck, Wouter Verbeke
2025 J jnl
Decision-centric fairness: Evaluation and optimization for resource allocation problems.
CoRR
Simon De Vos, Jente Van Belle, Andres Algaba, Wouter Verbeke, Sam Verboven
2025 J jnl
Estimating Treatment Effects in Networks using Domain Adversarial Training.
CoRR
Daan Caljon, Jente Van Belle, Wouter Verbeke
2025 J jnl
GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money Laundering.
CoRR
Bruno Deprez, Bart Baesens, Tim Verdonck, Wouter Verbeke
2025 J jnl
Inductive inference of gradient-boosted decision trees on graphs for insurance fraud detection.
CoRR
Félix Vandervorst, Bruno Deprez, Wouter Verbeke, Tim Verdonck
2025 J jnl
Predicting Employee Turnover: Scoping and Benchmarking the State-of-the-Art.
Bus. Inf. Syst. Eng.
Simon De Vos, Christopher Bockel-Rickermann, Jente Van Belle, Wouter Verbeke
2025 J jnl
To change or not to change the lead time in a dynamic order-up-to inventory system?
J. Oper. Res. Soc.
Jente Van Belle, Ruben Crevits, Tias Guns, Wouter Verbeke
2025 J jnl
Uncertainty in Machine Learning.
CoRR
Hans Weytjens, Wouter Verbeke
2025 J jnl
Understanding deep learning models for Length of Stay prediction on critically ill patients through latent space visualization.
Comput. Methods Programs Biomed.
Lyse Naomi Wamba Momo, Vincent Scheltjens, Wouter Verbeke, Frank E. Rademakers, Bart De Moor
2025 J jnl
Uplift Model Evaluation with Ordinal Dominance Graphs.
J. Mach. Learn. Res.
Brecht Verbeken, Marie-Anne Guerry, Wouter Verbeke, Sam Verboven
2025 J jnl
Using representation balancing to learn conditional-average dose responses from clustered data.
Trans. Mach. Learn. Res.
Christopher Bockel-Rickermann, Toon Vanderschueren, Jeroen Berrevoets, Tim Verdonck, Wouter Verbeke
2024 J jnl
A new perspective on classification: Optimally allocating limited resources to uncertain tasks.
Decis. Support Syst.
Toon Vanderschueren, Bart Baesens, Tim Verdonck, Wouter Verbeke
2024 J jnl
Claims fraud detection with uncertain labels.
Adv. Data Anal. Classif.
Félix Vandervorst, Wouter Verbeke, Tim Verdonck
2024 J jnl
Data-driven internal mobility: Similarity regularization gets the job done.
Knowl. Based Syst.
Simon De Vos, Johannes De Smedt, Marijke Verbruggen, Wouter Verbeke
2024 J jnl
Evaluating text classification: A benchmark study.
Expert Syst. Appl.
Manon Reusens, Alexander Stevens, Jonathan Tonglet, Johannes De Smedt, Wouter Verbeke, Seppe vanden Broucke, Bart Baesens
2024 J jnl
Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda.
Eur. J. Oper. Res.
Koen W. De Bock, Kristof Coussement, Arno De Caigny, Roman Slowinski, Bart Baesens, Robert N. Boute, Tsan-Ming Choi, Dursun Delen, Mathias Kraus, Stefan Lessmann, Sebastián Maldonado, David Martens, María Óskarsdóttir, Carla Vairetti, Wouter Verbeke, Richard Weber
2024 J jnl
Metalearners for Ranking Treatment Effects.
CoRR
Toon Vanderschueren, Wouter Verbeke, Felipe Moraes, Hugo Manuel Proença
2024 J jnl
Network Analytics for Anti-Money Laundering - A Systematic Literature Review and Experimental Evaluation.
CoRR
Bruno Deprez, Toon Vanderschueren, Bart Baesens, Tim Verdonck, Wouter Verbeke
2024 J jnl
Optimizing Treatment Allocation in the Presence of Interference.
CoRR
Daan Caljon, Jente Van Belle, Jeroen Berrevoets, Wouter Verbeke
2024 J jnl
Probabilistic Forecasting With Modified N-BEATS Networks.
IEEE Trans. Neural Networks Learn. Syst.
Jente Van Belle, Ruben Crevits, Daan Caljon, Wouter Verbeke
2024 J jnl
Sources of Gain: Decomposing Performance in Conditional Average Dose Response Estimation.
CoRR
Christopher Bockel-Rickermann, Toon Vanderschueren, Tim Verdonck, Wouter Verbeke
2024 J jnl
Target informed client recruitment for efficient federated learning in healthcare.
BMC Medical Informatics Decis. Mak.
Vincent Scheltjens, Lyse Naomi Wamba Momo, Wouter Verbeke, Bart De Moor
2024 J jnl
Uplift modeling with continuous treatments: A predict-then-optimize approach.
CoRR
Simon De Vos, Christopher Bockel-Rickermann, Stefan Lessmann, Wouter Verbeke
2024 J jnl
Using dynamic loss weighting to boost improvements in forecast stability.
CoRR
Daan Caljon, Jeff Vercauteren, Simon De Vos, Wouter Verbeke, Jente Van Belle
2023 J jnl
A Causal Perspective on Loan Pricing: Investigating the Impacts of Selection Bias on Identifying Bid-Response Functions.
CoRR
Christopher Bockel-Rickermann, Sam Verboven, Tim Verdonck, Wouter Verbeke
2023 A* conf
Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time.
ICML
Toon Vanderschueren, Alicia Curth, Wouter Verbeke, Mihaela van der Schaar
2023 J jnl
Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time.
CoRR
Toon Vanderschueren, Alicia Curth, Wouter Verbeke, Mihaela van der Schaar
2023 B conf
Client Recruitment for Federated Learning in ICU Length of Stay Prediction.
e-Science
Vincent Scheltjens, Lyse Naomi Wamba Momo, Wouter Verbeke, Bart De Moor
2023 J jnl
Client Recruitment for Federated Learning in ICU Length of Stay Prediction.
CoRR
Vincent Scheltjens, Lyse Naomi Wamba Momo, Wouter Verbeke, Bart De Moor
2023 J jnl
Fraud analytics: A decade of research: Organizing challenges and solutions in the field.
Expert Syst. Appl.
Christopher Bockel-Rickermann, Tim Verdonck, Wouter Verbeke
2023 J jnl
HydaLearn.
Appl. Intell.
Sam Verboven, Muhammad Hafeez Chaudhary, Jeroen Berrevoets, Vincent Ginis, Wouter Verbeke
2023 J jnl
Learning continuous-valued treatment effects through representation balancing.
CoRR
Christopher Bockel-Rickermann, Toon Vanderschueren, Jeroen Berrevoets, Tim Verdonck, Wouter Verbeke
2023 — ed.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I
PKDD/ECML Workshops (1)
Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami
2023 — ed.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II
PKDD/ECML Workshops (2)
Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami
2023 J jnl
NOFLITE: Learning to Predict Individual Treatment Effect Distributions.
Trans. Mach. Learn. Res.
Toon Vanderschueren, Jeroen Berrevoets, Wouter Verbeke
2023 J jnl
Robust instance-dependent cost-sensitive classification.
Adv. Data Anal. Classif.
Simon De Vos, Toon Vanderschueren, Tim Verdonck, Wouter Verbeke
2023 — conf
Timed Process Interventions: Causal Inference vs. Reinforcement Learning.
Business Process Management Workshops
Hans Weytjens, Wouter Verbeke, Jochen De Weerdt
2023 J jnl
Timing Process Interventions with Causal Inference and Reinforcement Learning.
CoRR
Hans Weytjens, Wouter Verbeke, Jochen De Weerdt
2023 J jnl
To do or not to do? Cost-sensitive causal classification with individual treatment effect estimates.
Eur. J. Oper. Res.
Wouter Verbeke, Diego Olaya, Marie-Anne Guerry, Jente Van Belle
2023 J jnl
Uplift vs. predictive modeling: a theoretical analysis.
CoRR
Théo Verhelst, Robin Petit, Wouter Verbeke, Gianluca Bontempi
2022 J jnl
A new perspective on classification: optimally allocating limited resources to uncertain tasks.
CoRR
Toon Vanderschueren, Bart Baesens, Tim Verdonck, Wouter Verbeke
2022 J jnl
Cost-sensitive ensemble learning: a unifying framework.
Data Min. Knowl. Discov.
George Petrides, Wouter Verbeke
2022 J jnl
Cost-sensitive learning for profit-driven credit scoring.
J. Oper. Res. Soc.
George Petrides, Darie Moldovan, Lize Coenen, Tias Guns, Wouter Verbeke
2022 J jnl
Data misrepresentation detection for insurance underwriting fraud prevention.
Decis. Support Syst.
Félix Vandervorst, Wouter Verbeke, Tim Verdonck
2022 J jnl
Fraud Analytics: A Decade of Research - Organizing Challenges and Solutions in the Field.
CoRR
Christopher Bockel-Rickermann, Tim Verdonck, Wouter Verbeke
2022 J jnl
Instance-dependent cost-sensitive learning for detecting transfer fraud.
Eur. J. Oper. Res.
Sebastiaan Höppner, Bart Baesens, Wouter Verbeke, Tim Verdonck
2022 — conf
Instance-dependent cost-sensitive learning: do we really need it?
HICSS
Toon Vanderschueren, Wouter Verbeke, Bart Baesens, Tim Verdonck
2022 — conf
Introduction to the Minitrack on Fraud Detection Using Machine Learning.
HICSS
Tim Verdonck, Wouter Verbeke, Maria Óskarsdóttir, Bart Baesens
2022 J jnl
Learning to Rank for Uplift Modeling.
IEEE Trans. Knowl. Data Eng.
Floris Devriendt, Jente Van Belle, Tias Guns, Wouter Verbeke
2022 J jnl
Machine learning methods for short-term probability of default: A comparison of classification, regression and ranking methods.
J. Oper. Res. Soc.
Lize Coenen, Wouter Verbeke, Tias Guns
2022 J jnl
Predict-then-optimize or predict-and-optimize? An empirical evaluation of cost-sensitive learning strategies.
Inf. Sci.
Toon Vanderschueren, Tim Verdonck, Bart Baesens, Wouter Verbeke
2022 J jnl
Prescriptive maintenance with causal machine learning.
CoRR
Toon Vanderschueren, Robert N. Boute, Tim Verdonck, Bart Baesens, Wouter Verbeke
2022 J jnl
Weight-of-evidence through shrinkage and spline binning for interpretable nonlinear classification.
Appl. Soft Comput.
Jakob Raymaekers, Wouter Verbeke, Tim Verdonck
2021 J jnl
Autoencoders for strategic decision support.
Decis. Support Syst.
Sam Verboven, Jeroen Berrevoets, Chris Wuytens, Bart Baesens, Wouter Verbeke
2021 J jnl
Redefining profit metrics for boosting student retention in higher education.
Decis. Support Syst.
Sebastián Maldonado, Jaime Miranda, Diego Olaya, Jonathan Vásquez, Wouter Verbeke
2021 J jnl
To do or not to do: cost-sensitive causal decision-making.
CoRR
Diego Olaya, Wouter Verbeke, Jente Van Belle, Marie-Anne Guerry
2021 J jnl
Using shared sell-through data to forecast wholesaler demand in multi-echelon supply chains.
Eur. J. Oper. Res.
Jente Van Belle, Tias Guns, Wouter Verbeke
2021 J jnl
Weight-of-evidence 2.0 with shrinkage and spline-binning.
CoRR
Jakob Raymaekers, Wouter Verbeke, Tim Verdonck
2021 J jnl
Why you should stop predicting customer churn and start using uplift models.
Inf. Sci.
Floris Devriendt, Jeroen Berrevoets, Wouter Verbeke
2020 J jnl
A Comparative Study of Social Network Classifiers for Predicting Churn in the Telecommunication Industry.
CoRR
María Óskarsdóttir, Cristián Bravo, Wouter Verbeke, Carlos Sarraute, Bart Baesens, Jan Vanthienen
2020 J jnl
A Model for Range Estimation and Energy-Efficient Routing of Electric Vehicles in Real-World Conditions.
IEEE Trans. Intell. Transp. Syst.
Cedric De Cauwer, Wouter Verbeke, Joeri Van Mierlo, Thierry Coosemans
2020 J jnl
A study of the U.S. domestic air transportation network: Temporal evolution of network topology and robustness from 2001 to 2016.
CoRR
Leonidas Siozos-Rousoulis, Dimitri Robert, Wouter Verbeke
2020 J jnl
A survey and benchmarking study of multitreatment uplift modeling.
Data Min. Knowl. Discov.
Diego Olaya, Kristof Coussement, Wouter Verbeke
2020 J jnl
Autoencoders for strategic decision support.
CoRR
Sam Verboven, Jeroen Berrevoets, Chris Wuytens, Bart Baesens, Wouter Verbeke
2020 J jnl
HydaLearn: Highly Dynamic Task Weighting for Multi-task Learning with Auxiliary Tasks.
CoRR
Sam Verboven, Muhammad Hafeez Chaudhary, Jeroen Berrevoets, Wouter Verbeke
2020 J jnl
Learning to rank for uplift modeling.
CoRR
Floris Devriendt, Tias Guns, Wouter Verbeke
2020 J jnl
Misclassification cost-sensitive ensemble learning: A unifying framework.
CoRR
George Petrides, Wouter Verbeke
2020 J jnl
Social Network Analytics for Churn Prediction in Telco: Model Building, Evaluation and Network Architecture.
CoRR
María Óskarsdóttir, Cristián Bravo, Wouter Verbeke, Carlos Sarraute, Bart Baesens, Jan Vanthienen
2020 J jnl
The foundations of cost-sensitive causal classification.
CoRR
Wouter Verbeke, Diego Olaya, Jeroen Berrevoets, Sebastián Maldonado
2020 J jnl
Uplift Modeling for preventing student dropout in higher education.
Decis. Support Syst.
Diego Olaya, Jonathan Vásquez, Sebastián Maldonado, Jaime Miranda, Wouter Verbeke
2019 J jnl
Causal Simulations for Uplift Modeling.
CoRR
Jeroen Berrevoets, Wouter Verbeke
2019 J jnl
Monitoring Urban-Freight Transport Based on GPS Trajectories of Heavy-Goods Vehicles.
IEEE Trans. Intell. Transp. Syst.
Sheida Hadavi, Sara Verlinde, Wouter Verbeke, Cathy Macharis, Tias Guns
2019 J jnl
Optimising Individual-Treatment-Effect Using Bandits.
CoRR
Jeroen Berrevoets, Sam Verboven, Wouter Verbeke
2019 J jnl
Reducing inferior member community participation using uplift modeling: Evidence from a field experiment.
Decis. Support Syst.
Steven Debaere, Floris Devriendt, Johanna Brunneder, Wouter Verbeke, Tom de Ruyck, Kristof Coussement
2018 J jnl
A Literature Survey and Experimental Evaluation of the State-of-the-Art in Uplift Modeling: A Stepping Stone Toward the Development of Prescriptive Analytics.
Big Data
Floris Devriendt, Darie Moldovan, Wouter Verbeke
2018 J jnl
A Robust profit measure for binary classification model evaluation.
Expert Syst. Appl.
Franco Garrido, Wouter Verbeke, Cristián Bravo
2018 J jnl
Special Issue on Profit-Driven Analytics.
Big Data
Bart Baesens, Wouter Verbeke, Cristián Bravo
2017 J jnl
RULEM: A novel heuristic rule learning approach for ordinal classification with monotonicity constraints.
Appl. Soft Comput.
Wouter Verbeke, David Martens, Bart Baesens
2017 J jnl
Recommendation-Based Conceptual Modeling and Ontology Evolution Framework (CMOE+).
Bus. Inf. Syst. Eng.
Frederik Gailly, Nadejda Alkhaldi, Sven Casteleyn, Wouter Verbeke
2017 J jnl
Social network analytics for churn prediction in telco: Model building, evaluation and network architecture.
Expert Syst. Appl.
María Óskarsdóttir, Cristián Bravo, Wouter Verbeke, Carlos Sarraute, Bart Baesens, Jan Vanthienen
2016 B conf
A comparative study of social network classifiers for predicting churn in the telecommunication industry.
ASONAM
María Óskarsdóttir, Cristián Bravo, Wouter Verbeke, Carlos Sarraute, Bart Baesens, Jan Vanthienen
2014 J jnl
Predicting online channel acceptance with social network data.
Decis. Support Syst.
Thomas Verbraken, Frank Goethals, Wouter Verbeke, Bart Baesens
2014 J jnl
Profit optimizing customer churn prediction with Bayesian network classifiers.
Intell. Data Anal.
Thomas Verbraken, Wouter Verbeke, Bart Baesens
2014 J jnl
Social network analysis for customer churn prediction.
Appl. Soft Comput.
Wouter Verbeke, David Martens, Bart Baesens
2013 J jnl
A Novel Profit Maximizing Metric for Measuring Classification Performance of Customer Churn Prediction Models.
IEEE Trans. Knowl. Data Eng.
Thomas Verbraken, Wouter Verbeke, Bart Baesens
2012 J jnl
Data Mining Techniques for Software Effort Estimation: A Comparative Study.
IEEE Trans. Software Eng.
Karel Dejaeger, Wouter Verbeke, David Martens, Bart Baesens
2012 J jnl
New insights into churn prediction in the telecommunication sector: A profit driven data mining approach.
Eur. J. Oper. Res.
Wouter Verbeke, Karel Dejaeger, David Martens, Joon Hur, Bart Baesens
2012 — —
Profit driven data mining in massive customer networks: new insights and algorithms.
Wouter Verbeke
2011 J jnl
Building comprehensible customer churn prediction models with advanced rule induction techniques.
Expert Syst. Appl.
Wouter Verbeke, David Martens, Christophe Mues, Bart Baesens
2011 J jnl
Performance of classification models from a user perspective.
Decis. Support Syst.
David Martens, Jan Vanthienen, Wouter Verbeke, Bart Baesens
2011 — conf
Using Social Network Classifiers for Predicting E-Commerce Adoption.
WEB
Thomas Verbraken, Frank Goethals, Wouter Verbeke, Bart Baesens
2010 — conf
Software Effort Prediction Using Regression Rule Extraction from Neural Networks.
ICTAI (2)
Rudy Setiono, Karel Dejaeger, Wouter Verbeke, David Martens, Bart Baesens
2009 — conf
Including Domain Knowledge in Customer Churn Prediction Using AntMiner+.
DMM@ICDM
Wouter Verbeke, Bart Baesens, David Martens, Manu De Backer, Raf Haesen