Publications
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
Workshop page
Partial counterfactual identification and uplift modeling: theoretical results and real-world assessment
Théo Verhelst, Denis Mercier, Jeevan Shrestha, Gianluca Bontempi
Machine Learning, 2023
Full paper – Read-only full text – arXiv
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 (DS 2021)
Full paper
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
Full paper
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 (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019)
Full paper
Churn Prediction and Causal Analysis on Telecom Customer Data
Théo Verhelst, supervised by Gianluca Bontempi
Université Libre de Bruxelles, 2019
Master thesis