| 2025 | AISTATS | Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis. | Rmi Khellaf, Aurlien Bellet, Julie Josse |
| 2025 | AISTATS | Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments. | Houssam Zenati, Judith Abcassis, Julie Josse, Bertrand Thirion |
| 2025 | ICML | Quantifying Treatment Effects: Estimating Risk Ratios via Observational Studies. | Ahmed Boughdiri, Julie Josse, Erwan Scornet |
| 2024 | AISTATS | MMD-based Variable Importance for Distributional Random Forest. | Clment Bnard, Jeffrey Nf, Julie Josse |
| 2024 | AISTATS | Positivity-free Policy Learning with Observational Data. | Pan Zhao, Antoine Chambaz, Julie Josse, Shu Yang |
| 2023 | ICML | Conformal Prediction with Missing Values. | Margaux Zaffran, Aymeric Dieuleveut, Julie Josse, Yaniv Romano |
| 2022 | ICML | Adaptive Conformal Predictions for Time Series. | Margaux Zaffran, Olivier Fron, Yannig Goude, Julie Josse, Aymeric Dieuleveut |
| 2020 | AISTATS | Linear predictor on linearly-generated data with missing values: non consistency and solutions. | Marine Le Morvan, Nicolas Prost, Julie Josse, Erwan Scornet, Gal Varoquaux |
| 2020 | ICML | Missing Data Imputation using Optimal Transport. | Boris Muzellec, Julie Josse, Claire Boyer, Marco Cuturi |
| 2018 | ESANN | Analysis of imputation bias for feature selection with missing data. | Borja Seijo-Pardo, Amparo Alonso-Betanzos, Kristin P. Bennett, Vernica Boln-Canedo, Isabelle Guyon, Julie Josse, Mehreen Saeed |
| 2015 | ICCS | Stable Autoencoding: A Flexible Framework for Regularized Low-rank Matrix Estimation. | Julie Josse, Stefan Wager |