Understanding Telecom Customer Churn with Machine Learning: From Prediction to Causal Inference. - Théo Verhelst; Olivier Caelen; Jean-Christophe Dewitte; Bertrand Lebichot; Gianluca Bontempi (BNAIC/BENELEARN (Selected Papers), 2019)

Predicting Reach to Find Persuadable Customers: Improving Uplift Models for Churn Prevention. - Théo Verhelst; Jeevan Shrestha; Denis Mercier; Jean-Christophe Dewitte; Gianluca Bontempi (DS, 2021)

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)

A Churn Prediction Dataset from the Telecom Sector: A New Benchmark for Uplift Modeling. - Théo Verhelst; Denis Mercier; Jeevan Shrestha; Gianluca Bontempi (PKDD/ECML Workshops (4), 2023)

Uplift vs. predictive modeling: a theoretical analysis. - Théo Verhelst; Robin Petit; Wouter Verbeke; Gianluca Bontempi (CoRR, 2023)

Partial counterfactual identification and uplift modeling: theoretical results and real-world assessment. - Théo Verhelst; Denis Mercier; Jeevan Shrestha; Gianluca Bontempi (Mach. Learn., 2024)

Probability of collision in nonlinear dynamics by moment propagation. - Théo Verhelst; Giacomo Acciarini; Dario Izzo; Francesco Biscani (CoRR, 2025)