Julie Josse

发表

Another Look at Bayesian Analysis of AMMI Models for Genotype-Environment Data

Hans-Peter Piepho, Julie Josse, Fred A. van Eeuwijk, 2014 .

Robust Lasso-Zero for sparse corruption and model selection with missing covariates

Julie Josse, Pascaline Descloux, Claire Boyer, 2020 .

A principal component method to impute missing values for mixed data

Julie Josse, Vincent Audigier, François Husson, 2013, Adv. Data Anal. Classif..

Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random Data

Julie Josse, Claire Boyer, Aude Sportisse, 2019, NeurIPS.

Miss

Julie Josse, Nathalie Vialaneix, Imke Mayer, 2020, Definitions.

Imputation of Mixed Data With Multilevel Singular Value Decomposition

Balasubramanian Narasimhan, Julie Josse, Franccois Husson, 2018, Journal of Computational and Graphical Statistics.

Testing the significance of the RV coefficient

Jérôme Pagès, Julie Josse, François Husson, 2008, Comput. Stat. Data Anal..

FactoMineR: An R Package for Multivariate Analysis

Sébastien Lê, Julie Josse, François Husson, 2008 .

Nonparametric Imputation by Data Depth

Julie Josse, Pavlo Mozharovskyi, Francois Husson, 2017, Journal of the American Statistical Association.

Dealing with missing data in model-based clustering through a MNAR model

Christophe Biernacki, Gilles Celeux, Julie Josse, 2018 .

Neumann networks: differential programming for supervised learning with missing values pdf

Gaël Varoquaux, Julie Josse, Erwan Scornet, 2020, NeurIPS.

Imputation and low-rank estimation with Missing Not At Random data

Julie Josse, Claire Boyer, Aude Sportisse, 2018, Statistics and Computing.

Bootstrap-Based Regularization for Low-Rank Matrix Estimation

Julie Josse, Stefan Wager, Stefan Wager, 2014, J. Mach. Learn. Res..

Causal inference methods for combining randomized trials and observational studies: a review

Shu Yang, Jean-Philippe Vert, Julie Josse, 2020, 2011.08047.

VARCLUST: clustering variables using dimensionality reduction

Julie Josse, Mateusz Staniak, Malgorzata Bogdan, 2020, 2011.06501.

Debiasing Averaged Stochastic Gradient Descent to handle missing values

Julie Josse, Claire Boyer, Aude Sportisse, 2020, NeurIPS.

Adaptive shrinkage of singular values

Julie Josse, Sylvain Sardy, S. Sardy, 2013, Statistics and Computing.

Logistic regression with missing covariates - Parameter estimation, model selection and prediction within a joint-modeling framework

Wei Jiang, Julie Josse, Marc Lavielle, 2018, Comput. Stat. Data Anal..

Linear predictor on linearly-generated data with missing values: non consistency and solutions pdf

Gael Varoquaux, Julie Josse, Erwan Scornet, 2020, AISTATS.

Regularised PCA to denoise and visualise data

Julie Josse, François Husson, Marie Verbanck, 2013, Stat. Comput..

Main Effects and Interactions in Mixed and Incomplete Data Frames

Robert Tibshirani, Julie Josse, Olga Klopp, 2018, Journal of the American Statistical Association.

Principal component analysis with missing values: a comparative survey of methods

Julie Josse, Stéphane Dray, S. Dray, 2015, Plant Ecology.

MIMCA: multiple imputation for categorical variables with multiple correspondence analysis

Julie Josse, Vincent Audigier, François Husson, 2015, Statistics and Computing.

Bayesian Dimensionality Reduction With PCA Using Penalized Semi-Integrated Likelihood

Julie Josse, Malgorzata Bogdan, Piotr Sobczyk, 2016, 1606.05333.

Doubly robust treatment effect estimation with missing attributes

Julie Josse, Stefan Wager, Imke Mayer, 2019 .

Some theoretical aspects of watermarking detection

Teddy Furon, Julie Josse, Sandrine Le Squin, 2006, Electronic Imaging.

MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models pdf

Jean-Philippe Vert, Julie Josse, Imke Mayer, 2020, ArXiv.

Analysis of imputation bias for feature selection with missing data

Verónica Bolón-Canedo, Amparo Alonso-Betanzos, Julie Josse, 2018, ESANN.

Selecting the number of components in principal component analysis using cross-validation approximations

Julie Josse, François Husson, J. Josse, 2012, Comput. Stat. Data Anal..

Some discussions on the Read Paper "Beyond subjective and objective in statistics" by A. Gelman and C. Hennig

Jean-Michel Marin, Christian P. Robert, Gilles Celeux, 2017 .

Biases in feature selection with missing data

Isabelle Guyon, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, 2019, Neurocomputing.

Multiple imputation in principal component analysis

Jérôme Pagès, Julie Josse, François Husson, 2011, Adv. Data Anal. Classif..

R for Statistics

Maela Kloareg, Julie Josse, Eric Matzner-Løber, 2012 .

Stable Autoencoding: A Flexible Framework for Regularized Low-Rank Matrix Estimation

Julie Josse, Stefan Wager, Stefan Wager, 2014, ICCS.

Empirical Bayes approaches to PageRank type algorithms for rating scientific journals

Gilles Celeux, Julie Josse, Jean-Louis Foulley, 2017 .

Low-rank model with covariates for count data with missing values

Julie Josse, Sylvain Sardy, Eric Moulines, 2019, J. Multivar. Anal..

CRAN Task View: Missing Data

Julie Josse, Nathalie Vialaneix, Nicholas Tierney, 2020 .

On the consistency of supervised learning with missing values pdf

Gaël Varoquaux, Julie Josse, Erwan Scornet, 2019, ArXiv.

Low-rank model with covariates for count data analysis

Julie Josse, Sylvain Sardy, Eric Moulines, 2017, 1703.02296.

Multiple correspondence analysis and the multilogit bilinear model

Julie Josse, William Fithian, William Fithian, 2017, J. Multivar. Anal..

Imputation de données manquantes pour des données mixtes via les méthodes factorielles grâce à missMDA

Julie Josse, Vincent Audigier, François Husson, 2012 .

Handling Missing Values with Regularized Iterative Multiple Correspondence Analysis

Marie Chavent, Julie Josse, François Husson, 2011, Journal of Classification.

Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames

Eric Moulines, Julie Josse, Hoi-To Wai, 2018, NeurIPS.

Handling missing values in exploratory multivariate data analysis methods

Julie Josse, François Husson, J. Josse, 2012 .

Missing Data Imputation using Optimal Transport

Julie Josse, Marco Cuturi, Claire Boyer, 2020, ICML.

Model-based clustering with missing not at random data. Missing mechanism

Christophe Biernacki, Gilles Celeux, Julie Josse, 2019 .

Model-based Clustering with Missing Not At Random Data pdf

Christophe Biernacki, Gilles Celeux, Julie Josse, 2021, ArXiv.

Causal effect on a target population: A sensitivity analysis to handle missing covariates

Julie Josse, Erwan Scornet, B'en'edicte Colnet, 2021, Journal of Causal Inference.

What's a good imputation to predict with missing values? pdf

Julie Josse, Erwan Scornet, Marine Le Morvan, 2021, NeurIPS.

Generalizing treatment effects with incomplete covariates

Julie Josse, Imke Mayer, Traumabase Group, 2021, 2104.12639.

Missing values in multi-level simultaneous component analysis

Julie Josse, Marieke E. Timmerman, Henk A. L. Kiers, 2013 .

Multinomial Multiple Correspondence Analysis

Julie Josse, Patrick J.F. Groenen, P. Groenen, 2016, 1603.03174.

Adaptive Bayesian SLOPE -- High-dimensional Model Selection with Missing Values

Wei Jiang, Julie Josse, Veronika Rockova, 2019 .

Principal component methods - hierarchical clustering - partitional clustering: why would we need to choose for visualizing data?

Julie Josse, J. Josse, 2010 .

Multiple Correspondence Analysis

Julie Josse, François Husson, 2014 .

denoiseR: A Package for Low Rank Matrix Estimation

Julie Josse, Sylvain Sardy, Stefan Wager, 2016, 1602.01206.

Multiple imputation for continuous variables using a Bayesian principal component analysis†

Julie Josse, Vincent Audigier, Franccois Husson, 2014, 1401.5747.