collaborators

12 papers

stat.ME2026

Causal Perspectives on Network Meta-Analysis

Ahmed Boughdiri, Francisco Andrade, Clément Berenfeld +1

Pairwise and network meta-analyses occupy the highest tier of evidence-based medicine and routinely inform clinical guidelines and healthcare decision-making. Current approaches ty…

cs.LG2026

Causal Evaluation of Membership Inference Attacks

Mathieu Even, Clément Berenfeld, Linus Bleistein +3

Membership Inference Attacks (MIAs) aim to distinguish training points (members) from unseen data (non-members), and are widely used to quantify memorization and assess privacy ris…

stat.ME2026

Estimating treatment duration effects via clone-censor-weight: a breast cancer case study

Charlotte Voinot, Noémie Simon-Tillaux, Emma Torrini +4

In this work, we study the estimation of treatment duration effects in observational survival data, where treatment and covariate histories evolve over time and longer observed dur…

cs.LG2026

Set-Valued Policy Learning

Laura Fuentes-Vicente, Mathieu Even, Gaëlle Dormion +3

Conventional treatment policies map patient covariates to a single recommended intervention in order to maximize expected clinical outcomes. Although a rich body of causal inferenc…

stat.ML2026

Principled Federated Random Forests for Heterogeneous Data

Rémi Khellaf, Erwan Scornet, Aurélien Bellet +1

Random Forests (RF) are among the most powerful and widely used predictive models for centralized tabular data, yet few methods exist to adapt them to the federated learning settin…

stat.ME2026

Causal Meta-Analysis: Rethinking the Foundations of Evidence-Based Medicine

Clément Berenfeld, Ahmed Boughdiri, Bénédicte Colnet +5

Meta-analysis, by synthesizing effect estimates from multiple studies conducted in diverse settings, stands at the top of the evidence hierarchy in clinical research. Yet, conventi…