Publications

Causal and predictive modeling of customer churn: lessons learned from empirical and theoretical research
Théo Verhelst, supervised by Gianluca Bontempi

PhD thesis – Université Libre de Bruxelles, 2024
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Uplift vs. predictive modeling: a theoretical analysis
Théo Verhelst, Robin Petit, Wouter Verbeke, Gianluca Bontempi

Preprint, 2023
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A churn prediction dataset from the telecom sector: a new benchmark for uplift modeling
Théo Verhelst, Denis Mercier, Jeevan Shrestha, Gianluca Bontempi

ECML PKDD 2023 Workshops - Workshop on Uplift Modeling and Causal Machine Learning for Operational Decision Making, 2023
Workshop pagearXivBibTeX

Partial counterfactual identification and uplift modeling: theoretical results and real-world assessment
Théo Verhelst, Denis Mercier, Jeevan Shrestha, Gianluca Bontempi

Machine Learning, 2023
Full paperRead-only full textarXivBibTeX

Predicting reach to find persuadable customers: improving uplift models for churn prevention
Théo Verhelst, Denis Mercier, Jeevan Shrestha, Jean-Christophe Dewitte, Gianluca Bontempi

24th International Conference on Discovery Science, 2021
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Transfer learning strategies for credit card fraud detection
Bertrand Lebichot, Théo Verhelst, Yann-Aël Le Borgne, Liyun He-Guelton, Frédéric Oblé, Gianluca Bontempi

IEEE Access, 2021
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Understanding telecom customer churn with machine learning: from prediction to causal inference
Théo Verhelst, Olivier Caelen, Jean-Christophe Dewitte, Bertrand Lebichot, Gianluca Bontempi

31st Benelux Conference on Artificial Intelligence and the 28th Belgian Dutch Conference on Machine Learning, 2019
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Churn Prediction and Causal Analysis on Telecom Customer Data
Théo Verhelst, supervised by Gianluca Bontempi

Master thesis – Université Libre de Bruxelles, 2019
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