Julie Josse

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 39

Top Topics

Multiple Imputation

Feature Selection

Categorical Variables

Top Venues

Publications

Pan Zhao, Antoine Chambaz, Julie Josse, Shu Yang
Positivity-free Policy Learning with Observational Data. AISTATS (2024)
Aude Sportisse, Matthieu Marbac, Fabien Laporte, Gilles Celeux, Claire Boyer, Julie Josse, Christophe Biernacki
Model-based clustering with missing not at random data. Stat. Comput. 34 (4) (2024)
Clément Bénard, Jeffrey Näf, Julie Josse
MMD-based Variable Importance for Distributional Random Forest. AISTATS (2024)
Margaux Zaffran, Aymeric Dieuleveut, Julie Josse, Yaniv Romano
Conformal Prediction with Missing Values. ICML (2023)
Clément Bénard, Jeffrey Näf, Julie Josse
MMD-based Variable Importance for Distributional Random Forest. CoRR (2023)
Pan Zhao, Antoine Chambaz, Julie Josse, Shu Yang
Positivity-free Policy Learning with Observational Data. CoRR (2023)
Margaux Zaffran, Aymeric Dieuleveut, Julie Josse, Yaniv Romano
Conformal Prediction with Missing Values. CoRR (2023)
Margaux Zaffran, Olivier Féron, Yannig Goude, Julie Josse, Aymeric Dieuleveut
Adaptive Conformal Predictions for Time Series. ICML (2022)
Margaux Zaffran, Aymeric Dieuleveut, Olivier Féron, Yannig Goude, Julie Josse
Adaptive Conformal Predictions for Time Series. CoRR (2022)
Imke Mayer, Aude Sportisse, Julie Josse, Nicholas J. Tierney, Nathalie Vialaneix
R-miss-tastic: a unified platform for missing values methods and workflows. R J. 14 (2) (2022)
Wei Jiang, Malgorzata Bogdan, Julie Josse, Szymon Majewski, Blazej Miasojedow, Veronika Rocková
Adaptive Bayesian SLOPE: Model Selection With Incomplete Data. J. Comput. Graph. Stat. 31 (1) (2022)
Alexandre Perez-Lebel, Gaël Varoquaux, Marine Le Morvan, Julie Josse, Jean-Baptiste Poline
Benchmarking missing-values approaches for predictive models on health databases. CoRR (2022)
Aude Sportisse, Christophe Biernacki, Claire Boyer, Julie Josse, Matthieu Marbac Lourdelle, Gilles Celeux, Fabien Laporte
Model-based Clustering with Missing Not At Random Data. CoRR (2021)
Marine Le Morvan, Julie Josse, Erwan Scornet, Gaël Varoquaux
What's a good imputation to predict with missing values? NeurIPS (2021)
Marine Le Morvan, Julie Josse, Erwan Scornet, Gaël Varoquaux
What's a good imputation to predict with missing values? CoRR (2021)
Marine Le Morvan, Nicolas Prost, Julie Josse, Erwan Scornet, Gaël Varoquaux
Linear predictor on linearly-generated data with missing values: non consistency and solutions. AISTATS (2020)
Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux
Neumann networks: differential programming for supervised learning with missing values. CoRR (2020)
Wei Jiang, Julie Josse, Marc Lavielle, TraumaBase Group
Logistic regression with missing covariates - Parameter estimation, model selection and prediction within a joint-modeling framework. Comput. Stat. Data Anal. 145 (2020)
Boris Muzellec, Julie Josse, Claire Boyer, Marco Cuturi
Missing Data Imputation using Optimal Transport. ICML (2020)
Marine Le Morvan, Nicolas Prost, Julie Josse, Erwan Scornet, Gaël Varoquaux
Linear predictor on linearly-generated data with missing values: non consistency and solutions. CoRR (2020)
Boris Muzellec, Julie Josse, Claire Boyer, Marco Cuturi
Missing Data Imputation using Optimal Transport. CoRR (2020)
Aude Sportisse, Claire Boyer, Aymeric Dieuleveut, Julie Josse
Debiasing Averaged Stochastic Gradient Descent to handle missing values. NeurIPS (2020)
Lucas Martin, Julie Josse, Bertrand Thirion
Multivariate Analysis is Sufficient for Lesion-Behaviour Mapping. BrainLes@MICCAI (1) (2020)
Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux
NeuMiss networks: differentiable programming for supervised learning with missing values. NeurIPS (2020)
Imke Mayer, Julie Josse, Félix Raimundo, Jean-Philippe Vert
MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models. CoRR (2020)
Aude Sportisse, Claire Boyer, Julie Josse
Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random Data. NeurIPS (2020)
Aude Sportisse, Claire Boyer, Julie Josse
Imputation and low-rank estimation with Missing Not At Random data. Stat. Comput. 30 (6) (2020)
Borja Seijo-Pardo, Amparo Alonso-Betanzos, Kristin P. Bennett, Verónica Bolón-Canedo, Julie Josse, Mehreen Saeed, Isabelle Guyon
Biases in feature selection with missing data. Neurocomputing 342 (2019)
Geneviève Robin, Julie Josse, Eric Moulines, Sylvain Sardy
Low-rank model with covariates for count data with missing values. J. Multivar. Anal. 173 (2019)
Julie Josse, Nicolas Prost, Erwan Scornet, Gaël Varoquaux
On the consistency of supervised learning with missing values. CoRR (2019)
Aude Sportisse, Claire Boyer, Julie Josse
Imputation and low-rank estimation with Missing Non At Random data. CoRR (2018)
Geneviève Robin, Hoi-To Wai, Julie Josse, Olga Klopp, Eric Moulines
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames. NeurIPS (2018)
Borja Seijo-Pardo, Amparo Alonso-Betanzos, Kristin P. Bennett, Verónica Bolón-Canedo, Isabelle Guyon, Julie Josse, Mehreen Saeed
Analysis of imputation bias for feature selection with missing data. ESANN (2018)
Geneviève Robin, Hoi-To Wai, Julie Josse, Olga Klopp, Eric Moulines
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames. CoRR (2018)
William Fithian, Julie Josse
Multiple correspondence analysis and the multilogit bilinear model. J. Multivar. Anal. 157 (2017)
Vincent Audigier, François Husson, Julie Josse
MIMCA: multiple imputation for categorical variables with multiple correspondence analysis. Stat. Comput. 27 (2) (2017)
Julie Josse, Stefan Wager
Bootstrap-Based Regularization for Low-Rank Matrix Estimation. J. Mach. Learn. Res. 17 (2016)
Vincent Audigier, François Husson, Julie Josse
A principal component method to impute missing values for mixed data. Adv. Data Anal. Classif. 10 (1) (2016)
Julie Josse, Sylvain Sardy
Adaptive shrinkage of singular values. Stat. Comput. 26 (3) (2016)
Marie Verbanck, Julie Josse, François Husson
Regularised PCA to denoise and visualise data. Stat. Comput. 25 (2) (2015)
Julie Josse, Stefan Wager
Stable Autoencoding: A Flexible Framework for Regularized Low-rank Matrix Estimation. ICCS (2015)
Julie Josse, Stefan Wager
Stable Autoencoding: A Flexible Framework for Regularized Low-Rank Matrix Estimation. CoRR (2014)
Julie Josse, François Husson
Selecting the number of components in principal component analysis using cross-validation approximations. Comput. Stat. Data Anal. 56 (6) (2012)
Julie Josse, Marie Chavent, Benoit Liquet, François Husson
Handling Missing Values with Regularized Iterative Multiple Correspondence Analysis. J. Classif. 29 (1) (2012)
Julie Josse, Jérôme Pagès, François Husson
Multiple imputation in principal component analysis. Adv. Data Anal. Classif. 5 (3) (2011)
Julie Josse, Jérôme Pagès, François Husson
Testing the significance of the RV coefficient. Comput. Stat. Data Anal. 53 (1) (2008)
Teddy Furon, Julie Josse, Sandrine Le Squin
Some theoretical aspects of watermarking detection. Security, Steganography, and Watermarking of Multimedia Contents (2006)