Bontempi's research on causality
Papers
- Bontempi, Gianluca; Meyer, Patrick E "Causal filter selection in microarray data", Proceedings of the 27th international conference on machine learning, ICML10, 95-102, 2010,
- Olsen, Catharina; Meyer, Patrick E; Bontempi, Gianluca; "Inferring causal relationships using information theoretic measures", Proceedings of the 5th Benelux Bioinformatics Conference (BBC09), 2009,
- Bontempi, Gianluca; Haibe-Kains, Benjamin; Desmedt, Christine; Sotiriou, Christos; Quackenbush, John; "Multiple-input multiple-output causal strategies for gene selection", BMC Bioinformatics, 12, 1-13, 2011, BioMed Central
- Bontempi, Gianluca; Flauder, Maxime; "From dependency to causality: a machine learning approach", J. Mach. Learn. Res., 16,1,2437-2457,2015,
- Verhelst, Théo; Caelen, Olivier; Dewitte, Jean-Christophe; Lebichot, Bertrand; Bontempi, Gianluca; "Understanding telecom customer churn with machine learning: from prediction to causal inference", Artificial Intelligence and Machine Learning: 31st Benelux AI Conference, BNAIC 2019, and 28th Belgian-Dutch Machine Learning Conference, BENELEARN 2019, Brussels, Belgium, November 6-8, 2019,182-200,2020, Springer International Publishing
- Verhelst, Théo; Shrestha, Jeevan; Mercier, Denis; Dewitte, Jean-Christophe; Bontempi, Gianluca; "Predicting reach to find persuadable customers: Improving uplift models for churn prevention", Discovery Science: 24th International Conference, DS 2021, Halifax, NS, Canada, October 11–13, 2021, Proceedings 24", 44-54,2021,Springer International Publishing
- Verhelst, Théo; Mercier, Denis; Shrestha, Jeevan; Bontempi, Gianluca; "Partial counterfactual identification and uplift modeling: theoretical results and real-world assessment", Machine Learning, 113, 3, 1043-1067, 2024, Springer US New York
- Verhelst, Théo; Petit, Robin; Verbeke, Wouter; Bontempi, Gianluca; "Uplift vs. predictive modeling: a theoretical analysis", arXiv preprint arXiv:2309.12036,2023,
- Paldino, Gian Marco; Bontempi, Gianluca; "Causal discovery in multivariate time series through mutual information featurization", International Journal of Forecasting, 2026,Elsevier
- Paldino, Gian Marco; Caelen, Olivier; Oueslati, Marouene; Ansay, Marc; Johanesa, Tojo Valisoa A; Bontempi, Gianluca; "On the integration of domain adaptation and causal discovery in digital twins: A case study for plastic injection molding", Future Generation Computer Systems,108427, 2026, North-Holland
- Svinin, Gleb; Loo, Rebecca Ting Jiin; Kumar, Nikhilesh Vasantha; Murthy, Varsha Venkatesha; Odongo, Dilara Uzuner; Díaz-Uriarte, Ramón; Conesa, Ana; Bontempi, Gianluca; Vinga, Susana; Granata, Ilaria; "Ten quick tips for causal analysis of biomedical omics data", PLoS computational biology, 22, 8, e1014668,2026,"Public Library of Science San Francisco, CA USA
- Verhelst, Théo; Bontempi, Gianluca; "Identifying counterfactual probabilities using bivariate distributions and uplift modeling", Proceedings of the ESANN conference 2026
Lectures
- 2020: Politecnico di Milano summer school "From supervised learning to causal inference in large dimensional settings", PhD Course,
- 2020 French-German Summer School with Industry on ML, AI "Causality and big data analytics: risk, challenges and perspectives"
- 2020 Keynote at Models and Learning in Clustering and Classification (MBC) conference "From supervised learning to causal inference"
- 2023: IRIDTA BigDat23 Summer School "Big Data Analytics in Fraud Detection and Churn Prevention: from Prediction to Causal Inference "
- 2023: IEEE BigData23 Tutorial Big Data Analytics in Fraud Detection and Churn Prevention: from Prediction to Causal Inference