Julie Josse - RankMe

62 papers A* 9A 5B 1Misc 1Journal 44Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Membership Inference Attacks from Causal Principles. CoRR Mathieu Even, Clément Berenfeld, Linus Bleistein, Tudor Cebere, Julie Josse, Aurélien Bellet
2026	J	`jnl`	Preference-based Conditional Treatment Effects and Policy Learning. CoRR Dovid Parnas, Mathieu Even, Julie Josse, Uri Shalit
2026	J	`jnl`	Principled Federated Random Forests for Heterogeneous Data. CoRR Rémi Khellaf, Erwan Scornet, Aurélien Bellet, Julie Josse
2025	A	`conf`	Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments. AISTATS Houssam Zenati, Judith Abécassis, Julie Josse, Bertrand Thirion
2025	J	`jnl`	Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments. CoRR Houssam Zenati, Judith Abécassis, Julie Josse, Bertrand Thirion
2025	J	`jnl`	Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data. J. Mach. Learn. Res. Pan Zhao, Julie Josse, Shu Yang
2025	J	`jnl`	Federated Causal Inference from Multi-Site Observational Data via Propensity Score Aggregation. CoRR Rémi Khellaf, Aurélien Bellet, Julie Josse
2025	A	`conf`	Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis. AISTATS Rémi Khellaf, Aurélien Bellet, Julie Josse
2025	J	`jnl`	Model Agnostic Differentially Private Causal Inference. CoRR Christian Janos Lebeda, Mathieu Even, Aurélien Bellet, Julie Josse
2025	J	`jnl`	Optimal Transport with Heterogeneously Missing Data. CoRR Linus Bleistein, Aurélien Bellet, Julie Josse
2025	J	`jnl`	Probabilistic prediction of arrivals and hospitalizations in emergency departments in Île-de-France. Int. J. Medical Informatics Herbert Susmann, Antoine Chambaz, Julie Josse, Philippe Aegerter, Mathias Wargon, Emmanuel Bacry
2025	A*	`conf`	Quantifying Treatment Effects: Estimating Risk Ratios via Observational Studies. ICML Ahmed Boughdiri, Julie Josse, Erwan Scornet
2025	J	`jnl`	When Pattern-by-Pattern Works: Theoretical and Empirical Insights for Logistic Models with Missing Values. CoRR Christophe Muller, Erwan Scornet, Julie Josse
2024	J	`jnl`	Expert Study on Interpretable Machine Learning Models with Missing Data. CoRR Lena Stempfle, Arthur James, Julie Josse, Tobias Gauss, Fredrik D. Johansson
2024	J	`jnl`	Federated Causal Inference: Multi-Centric ATE Estimation beyond Meta-Analysis. CoRR Rémi Khellaf, Aurélien Bellet, Julie Josse
2024	A	`conf`	MMD-based Variable Importance for Distributional Random Forest. AISTATS Clément Bénard, Jeffrey Näf, Julie Josse
2024	J	`jnl`	Model-based clustering with missing not at random data. Stat. Comput. Aude Sportisse, Matthieu Marbac, Fabien Laporte, Gilles Celeux, Claire Boyer, Julie Josse, Christophe Biernacki
2024	A	`conf`	Positivity-free Policy Learning with Observational Data. AISTATS Pan Zhao, Antoine Chambaz, Julie Josse, Shu Yang
2023	A*	`conf`	Conformal Prediction with Missing Values. ICML Margaux Zaffran, Aymeric Dieuleveut, Julie Josse, Yaniv Romano
2023	J	`jnl`	Conformal Prediction with Missing Values. CoRR Margaux Zaffran, Aymeric Dieuleveut, Julie Josse, Yaniv Romano
2023	J	`jnl`	MMD-based Variable Importance for Distributional Random Forest. CoRR Clément Bénard, Jeffrey Näf, Julie Josse
2023	J	`jnl`	Positivity-free Policy Learning with Observational Data. CoRR Pan Zhao, Antoine Chambaz, Julie Josse, Shu Yang
2022	J	`jnl`	Adaptive Bayesian SLOPE: Model Selection With Incomplete Data. J. Comput. Graph. Stat. Wei Jiang, Malgorzata Bogdan, Julie Josse, Szymon Majewski, Blazej Miasojedow, Veronika Rocková
2022	A*	`conf`	Adaptive Conformal Predictions for Time Series. ICML Margaux Zaffran, Olivier Féron, Yannig Goude, Julie Josse, Aymeric Dieuleveut
2022	J	`jnl`	Adaptive Conformal Predictions for Time Series. CoRR Margaux Zaffran, Aymeric Dieuleveut, Olivier Féron, Yannig Goude, Julie Josse
2022	J	`jnl`	Benchmarking missing-values approaches for predictive models on health databases. CoRR Alexandre Perez-Lebel, Gaël Varoquaux, Marine Le Morvan, Julie Josse, Jean-Baptiste Poline
2022	J	`jnl`	R-miss-tastic: a unified platform for missing values methods and workflows. R J. Imke Mayer, Aude Sportisse, Julie Josse, Nicholas J. Tierney, Nathalie Vialaneix
2021	J	`jnl`	Model-based Clustering with Missing Not At Random Data. CoRR Aude Sportisse, Christophe Biernacki, Claire Boyer, Julie Josse, Matthieu Marbac Lourdelle, Gilles Celeux, Fabien Laporte
2021	A*	`conf`	What's a good imputation to predict with missing values? NeurIPS Marine Le Morvan, Julie Josse, Erwan Scornet, Gaël Varoquaux
2021	J	`jnl`	What's a good imputation to predict with missing values? CoRR Marine Le Morvan, Julie Josse, Erwan Scornet, Gaël Varoquaux
2020	A*	`conf`	Debiasing Averaged Stochastic Gradient Descent to handle missing values. NeurIPS Aude Sportisse, Claire Boyer, Aymeric Dieuleveut, Julie Josse
2020	A*	`conf`	Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random Data. NeurIPS Aude Sportisse, Claire Boyer, Julie Josse
2020	J	`jnl`	Imputation and low-rank estimation with Missing Not At Random data. Stat. Comput. Aude Sportisse, Claire Boyer, Julie Josse
2020	A	`conf`	Linear predictor on linearly-generated data with missing values: non consistency and solutions. AISTATS Marine Le Morvan, Nicolas Prost, Julie Josse, Erwan Scornet, Gaël Varoquaux
2020	J	`jnl`	Linear predictor on linearly-generated data with missing values: non consistency and solutions. CoRR Marine Le Morvan, Nicolas Prost, Julie Josse, Erwan Scornet, Gaël Varoquaux
2020	J	`jnl`	Logistic regression with missing covariates - Parameter estimation, model selection and prediction within a joint-modeling framework. Comput. Stat. Data Anal. Wei Jiang, Julie Josse, Marc Lavielle, TraumaBase Group
2020	J	`jnl`	MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models. CoRR Imke Mayer, Julie Josse, Félix Raimundo, Jean-Philippe Vert
2020	A*	`conf`	Missing Data Imputation using Optimal Transport. ICML Boris Muzellec, Julie Josse, Claire Boyer, Marco Cuturi
2020	J	`jnl`	Missing Data Imputation using Optimal Transport. CoRR Boris Muzellec, Julie Josse, Claire Boyer, Marco Cuturi
2020	—	`conf`	Multivariate Analysis is Sufficient for Lesion-Behaviour Mapping. BrainLes@MICCAI (1) Lucas Martin, Julie Josse, Bertrand Thirion
2020	A*	`conf`	NeuMiss networks: differentiable programming for supervised learning with missing values. NeurIPS Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux
2020	J	`jnl`	Neumann networks: differential programming for supervised learning with missing values. CoRR Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux
2019	J	`jnl`	Biases in feature selection with missing data. Neurocomputing Borja Seijo-Pardo, Amparo Alonso-Betanzos, Kristin P. Bennett, Verónica Bolón-Canedo, Julie Josse, Mehreen Saeed, Isabelle Guyon
2019	J	`jnl`	Low-rank model with covariates for count data with missing values. J. Multivar. Anal. Geneviève Robin, Julie Josse, Eric Moulines, Sylvain Sardy
2019	J	`jnl`	On the consistency of supervised learning with missing values. CoRR Julie Josse, Nicolas Prost, Erwan Scornet, Gaël Varoquaux
2018	B	`conf`	Analysis of imputation bias for feature selection with missing data. ESANN Borja Seijo-Pardo, Amparo Alonso-Betanzos, Kristin P. Bennett, Verónica Bolón-Canedo, Isabelle Guyon, Julie Josse, Mehreen Saeed
2018	J	`jnl`	Imputation and low-rank estimation with Missing Non At Random data. CoRR Aude Sportisse, Claire Boyer, Julie Josse
2018	A*	`conf`	Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames. NeurIPS Geneviève Robin, Hoi-To Wai, Julie Josse, Olga Klopp, Eric Moulines
2018	J	`jnl`	Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames. CoRR Geneviève Robin, Hoi-To Wai, Julie Josse, Olga Klopp, Eric Moulines
2017	J	`jnl`	MIMCA: multiple imputation for categorical variables with multiple correspondence analysis. Stat. Comput. Vincent Audigier, François Husson, Julie Josse
2017	J	`jnl`	Multiple correspondence analysis and the multilogit bilinear model. J. Multivar. Anal. William Fithian, Julie Josse
2016	J	`jnl`	A principal component method to impute missing values for mixed data. Adv. Data Anal. Classif. Vincent Audigier, François Husson, Julie Josse
2016	J	`jnl`	Adaptive shrinkage of singular values. Stat. Comput. Julie Josse, Sylvain Sardy
2016	J	`jnl`	Bootstrap-Based Regularization for Low-Rank Matrix Estimation. J. Mach. Learn. Res. Julie Josse, Stefan Wager
2015	J	`jnl`	Regularised PCA to denoise and visualise data. Stat. Comput. Marie Verbanck, Julie Josse, François Husson
2015	Misc	`conf`	Stable Autoencoding: A Flexible Framework for Regularized Low-rank Matrix Estimation. ICCS Julie Josse, Stefan Wager
2014	J	`jnl`	Stable Autoencoding: A Flexible Framework for Regularized Low-Rank Matrix Estimation. CoRR Julie Josse, Stefan Wager
2012	J	`jnl`	Handling Missing Values with Regularized Iterative Multiple Correspondence Analysis. J. Classif. Julie Josse, Marie Chavent, Benoit Liquet, François Husson
2012	J	`jnl`	Selecting the number of components in principal component analysis using cross-validation approximations. Comput. Stat. Data Anal. Julie Josse, François Husson
2011	J	`jnl`	Multiple imputation in principal component analysis. Adv. Data Anal. Classif. Julie Josse, Jérôme Pagès, François Husson
2008	J	`jnl`	Testing the significance of the RV coefficient. Comput. Stat. Data Anal. Julie Josse, Jérôme Pagès, François Husson
2006	—	`conf`	Some theoretical aspects of watermarking detection. Security, Steganography, and Watermarking of Multimedia Contents Teddy Furon, Julie Josse, Sandrine Le Squin