Julie Josse

Research

Selected publications:

• Colnet, B.,Varoquaux, G., J.J. &  Scornet, E.. Risk ratio, odds ratio, risk difference… Which causal measure is easier to generalize? In revision. 2023.
• Colnet, B. et al. Causal inference methods for combining randomized trials and observational studies: a review. Statistical Science. 2020. 
• Mayer, I., J.J., Wager, S., Sverdr, E., Traumabase.  Doubly robust treatment effect estimation with incomplete confounders. Annals Of Applied Statistics. 2020.
• Le Morvan, J.J, E. Scornet & . What’s a good imputation to predict with missing values? Neurips 2021. (Spotlight).
• J.J., et al. On the consistency of supervised learning with missing values. Statistical paper. 2018-2024.
• J.J & Wager, S. Bootstrap-Based Regularization for Low-Rank Matrix Estimation. Journal of Machine Learning research. 2016.
• J.J & Husson, F. missMDA a package to handle missing values (imputation with PCA, PCA with missing values). Journal of Statistical Software. 2015

Current researchers collaborators: Judith Abecassis, Gosia Bogdan, Claire Boyer,  Antoine Chambaz, Yanniv Romano, Erwan Scornet, Bertrand Thirion, Shu Yang,
Current collaboration with companies:   EDF, Elixir Health, Quinten Health, Sanofi,  etc.
Current collaboration in health:   APHP, CHU Nancy/Montpellier, Gustave Roussy, Traumabase, etc.
Associate Editor: Foundations and Trends® in Machine Learning. Past:  Journal of Computational & Graphical Statistics.  Journal of Statistical Software. (7 years). AC for Neurips, ICLR.

– A summary of my research contributions up to 2023  can be found here.
– An overview of my research up to 2016 can be found in my Habilitation.  (slides)

Publications:

Year	Authors	Title	link
2024	Zaffran, M., Josse, J., Romano, Y., Dieuleveut, A.	Predictive Uncertainty Quantification with Missing Covariates	pdf
2024	Boughdiri, A., Josse, J. & Scornet, E.	Quantifying Treatment Effects: Estimating Risk Ratios in Causal Inference.	pdf
2024	Näf, J., & Josse, J.	What is a Good Imputation Under MAR Missingness?	pdf slides
2024	Sussman, H., Chambaz, A. & Josse, J, Aegerter, P. Wargon, M., Bacry E.	Probabilistic Prediction of Arrivals and Hospitalizations in Emergency Departments in Ile-de-France. Submitted.	pdf
2024	Zhao, P., Gatulle, N, James, A., Josse, J. & Chambaz, A.	Learning, Evaluating and Analysising An Individualized Decision Support Rule with Application to Early Intervention in Intensive Care Unit
2023	Bénard, C., Naf, J. & Josse, J.	MMD-based Variable Importance for Distributional Random Forest. AISTAT2024	pdf
2023	Sussman, H., Chambaz, A. & Josse, J.	Adaptive Conformal, an R package for adaptive conformal inference. Computo.	pdf
2023	Zhao, P., Chambaz, A., Josse, J., Yang, S.	Positivity-free Policy Learning with Observational Data. AISTAT2024	pdf
2023	Bénard, C, Josse, J.	Variable importance for causal forests: breaking down the heterogeneity of treatment effects Submitted.	pdf
2023	Colnet, B, Josse, J., Varoquaux, G., Scornet, E.	Risk ratio, odds ratio, risk difference... Which causal measure is easier to generalize? Submitted.	pdf
2023	Zaffran, Josse, J. M., Dieuleveut A., Romano, Y.	Conformal prediction with missing values. ICML2023.	pdf poster
2023	Zhao, P., Josse, J. & Yang, S.	(2023). Efficient and robust transfer learning of optimal individualized treatment regimes with right-censored survival data. Submitted.	pdf
2022-24	Colnet, B, Josse, J., Varoquaux, G., Scornet, E.	Reweighting the RCT for generalization: finite sample analysis and variable selection. JRSSA.	pdf
2022	Blet et al.	Association between in-ICU red blood cells transfusion and one-year mortality in ICU survivors. Critical Care.	pdf
2022	Colnet, B, Josse, J., Varoquaux, G., Scornet, E.	Generalizing a causal effect: sensitivity analysis and missing covariates. Journal of Causal Inference.	pdf slides
2022	Gauss et al.	Is Early Norepinephrine Associated with 24-hour Mortality of Blunt Trauma Patients in Haemorrhagic Shock? An International Cohort Study. Jama Network.	pdf
2022	Garaix et al.	Decision-making tools for healthcare structures in times of pandemic. Anaesthesia Critical Care & Pain Medicine.	pdf
2022	Zaffran et al.	Adaptive conformal prediction for time series. ICML2022.	pdf slides video
2022	Perez-Lebel et al.	Benchmarking missing-values approaches for predictive models on health databases. GigaScience.	pdf
2021	Le Morvan, J. Josse, E. Scornet. & G. Varoquaux	What’s a good imputation to predict with missing values? Neurips 2021. (Spotlight).	pdf video slides
2021	Sportisse, A. et al.	Model-based Clustering with Missing Not At Random Data. Submitted.	pdf
2021	Mayer, I., Josse, J & Traumbase	Transporting treatment effects with incomplete attributes. Biometrical Journal	pdf
2020-2023	Colnet, B et al.	Causal inference methods for combining randomized trials and observational studies: a review. Statistical Science.	pdf
2020	Le Morvan, J. Josse, M., Moreaux, T, E. Scornet. & G. Varoquaux	Neumiss networks: differential programming for supervised learning with missing values. Neurips2020. (Oral)	pdf slides video slides video
2020	Sbidian et al.	Hydroxychloroquine with or without azithromycin and in-hospital mortality or discharge in patients hospitalized for COVID-19 infection: a cohort study of 4,642 in-patients in France. Preprint.	pdf
2020	Consortium ICUBAM	ICU Bed Availability Monitoring and analysis in the Grand Est région of France during the COVID-19 epidemic. Statistiques et Société.	pdf slides
2020	A. Sportisse, C. Boyer, and Josse, J.	Estimation and imputation in Probabilistic Principal Component Analysis with Missing Not At Random data. Neurips2020.	pdf slides video code
2020	A. Sportisse, C. Boyer, A. Dieuleveut, J. Josse.	Debiasing Stochastic Gradient Descent to handle missing values. Neurips2020.	pdf slides
2020	J.D. Moyer et al.	Trauma reloaded: Trauma registry in the era of data science. Anaesthesia Critical Care & Pain Medicine.	pdf
2020	Muzellec, B., Josse, J. Boyer, C. & Cuturi, M.	Missing Data Imputation using Optimal Transport. ICML2020.	pdf slides videos code
2019	Josse, J., Mayer, I, & Vert, J.P.	MissDeepCausal: causal inference from incomplete data using deep latent variable models. Preprint.	pdf
2020	Le Morvan, M., N. Prost, J. Josse, E. Scornet. & G. Varoquaux	Linear predictor on linearly-generated data with missing values: non consistency and solutions. AISTAT2020.	pdf slides
2020	Descloux, P. , Boyer, C. Josse, J. Sportisse, A. Sardy, S.	Robust Lasso-Zero for sparse corruption and model selection with missing covariates. Scandinavian Journal of Statistics.	pdf
2022	Mayer, I, Sportisse, A., Josse, J., Vialaneix, N., Tierney, N.	R-miss-tastic: a unified platform for missing values methods and workflows. R journal.	pdf
2019-20	Mayer, I, Josse, J., Wager, S., Sverdr, E., Moyer, J.D. and Gauss, T.	Doubly robust treatment effect estimation with incomplete confounders. Annals Of Applied Statistics.	pdf code slides videos
2019-21	M. Bogdan, W. Jiang, J. Josse, B. Miasojedow and V. Rockova.	Adaptive Bayesian SLOPE – High dimensional Model Selection with Missing Values. Journal of Computational and Graphical Statistics.	pdf slides
2019-24	Josse, J., Prost, N., Scornet, E. & Varoquaux, G.	On the consistency of supervised learning with missing values. Statistical paper.	pdf slidescode slides
2019	G. Robin, O. Klopp, J. Josse, E. Moulines, and R. Tibshirani	Main effects and interactions in mixed and incomplete data frames. Journal of the American Statistical Association.	pdf Package
2019	Hamada, S et al.	Effect of Fibrinogen administration on early mortality in traumatic haemorrhagic shock: a propensity score analysis. Journal of Trauma.
2019	Sportisse, A., Boyer, C. and Josse, J.	Low-rank estimation with missing non at random data. Statistics and Computing.	pdf code
2018	Josse, J., Husson, F. Robin, G. and Balasubramanian. N.	Imputation of mixed data with multilevel SVD. Journal of Computational and Graphical Statistics.	pdf slides
2018	Robin, G, Sardy, S., Moulines, E. and Josse, J.	Low-rank model with covariates for count data with missing values. Journal of Multivariate Analysis.	pdf Package code
2018	Jiang, W., Lavielle, M. Josse, J. and T. Gauss.	Logistic Regression with Missing Covariates -- Parameter Estimation, Model Selection and Prediction within a Joint-Modeling Framework. CSDA.	pdf slides Package, code
2018	G. Robin, Hoi To Wai, J. Josse, O. Klopp and E. Moulines	Low-rank interactions and sparse additive effects model for large data frames. NeurIPS 2018.
2018	Josse, J. and Reiter, J.	Introduction to the Special Section on Missing Data. Statistical Sciences.	pdf
2018	Seijo-Pardo, B., Alonso-Betanzos, A., P. Bennett, K. Bol\'on-Canedo, Josse, J., Saeed, M., Guyon, I.	Feature selection in the presence of missing data. Neurocomputing, ESANN.
2017-2018	Mozharovskyi, P., Husson, F. and Josse, J.	Nonparametric imputation by data depth. Journal of the American Statistical Association.	pdf slides code
2017	Holmes, S and Josse, J.	50 years of data-sciences, discussion. Journal of Computational and Graphical Statistics.	pdf
2017	Bollmann, S., Cook, Di. Dumas, J., Fox, J., Josse, J., Keyes, O. Strobl, C., Turner, H. and Debelak, R.	A First Survey on the Diversity of the R Community. R journal.	pdf slides
2017	G. Celeux, J. Jewson, J. Josse, J.M. Marin and C. P. Robert.	Some discussions on the Read Paper "Beyond subjective and objective in statistics" by A. Gelman and C. Hennig.	pdf
2017	Foulley, JL, Celeux, G and Josse, J.	Empirical Bayes approaches to PageRank type algorithms for rating scientific journals. Technical report.	pdf slides
2016	Sobczyk, P, Bogdan, M. and Josse, J.	PCA using penalized semi-integrated likelihood. Journal of Computational and Graphical Statistics.	pdf
2016	Fithian, W. and Josse, J.	Multiple Correspondence Analysis & the Multilogit Bilinear Model. Journal of Multivariate Analysis.	pdf slides
2016	Husson, F., Josse, J. and Saporta, G.	Jan de Leeuw and the French school of data analysis. Journal of Statistical Software.	pdf
2016-2017	Josse, J., Sardy, S. and Wager, S.	denoiseR: a package for low rank matrix estimation. Preprint.	pdf Package
2016	Groenen, P. and Josse, J.	Multinomial Multiple Correspondence Analysis. Preprint.	pdf
2016	Fujii, H., Josse, J., Tanioka, M., Miyachi, Y. Husson, F., and Ono, M.	Regulatory T cells in melanoma revisited by a computational clustering of FOXP3+ T cell subpopulations. Journal of Immunology.	pdf
2015	Audigier, V., Husson, F. and Josse, J.	MIMCA: Multiple imputation for categorical variables with multiple correspondence analysis. Statistics and Computing.	pdf slides
2015-2016	Josse, J and Wager, S.	Bootstrap-Based Regularization for Low-Rank Matrix Estimation. Journal of Machine Learning research.	pdf slides
2015	Josse, J. and Sardy, S.	Adaptive Shrinkage of singular values. Statistics and Computing.	pdf
2015	Josse, J and Husson, F.	missMDA a package to handle missing values in and with multivariate data analysis methods. Journal of Statistical Software.	pdf
2015	Audigier, V., Husson, F. and Josse, J.	Multiple Imputation with Bayesian PCA.  Journal of Statistical Computation and Simulation.	pdf
2015-2016	Josse, J. and Holmes, S.	Measuring multivariate association. Statistics Survey.	pdf
2014	Audigier, V., Husson, F. and Josse, J.	A principal components method to impute mixed data.  Advances in Data analysis and Classification.	pdf slides
2014	Josse, J., Wager, S. and Husson, F.	Confidence areas for fixed-effects PCA.  Journal of Computational and Graphical Statistics.	pdf slides
2014	Dray, S and Josse, J.	Principal component analysis with missing values: a comparative survey of methods. Plant Ecology.	pdf
2014	Josse, J.,  van Eeuwijk, F., Piepho, H-P and Denis, J.B.	Another look at Bayesian analysis of AMMI models for genotype-environment data.  Journal of Agricultural, Biological, and Environmental Statistics.	pdf
2013	Verbanck, M., Josse, J. and Husson, F.	Regularized PCA to denoise and visualise data.  Statistics and Computing.	pdf
2013	Josse, J., Timmerman, M.E. and Kiers, H.A.L.	Missing values in multi-level simultaneous component analysis. Chemometrics and Intelligent Laboratory Systems.	pdf
2013	Husson, F. and Josse, J.	Handling missing values in Multiple Factor Analysis. Food Quality and Preferences.	pdf
2013	Josse, J and Husson, F.	Handling missing values in exploratory multivariate data analysis methods. Journal de la SFdS. Paper written for the best Ph.D doctoral thesis prize delivered by the French Statistical Society.	pdf
2012	Josse, J., Chavent, M., Liquet, B. and Husson, F.	Regularized Iterative Multiple Correspondence Analysis. Journal of Classification.	pdf
2011	Josse, J and Husson, F.	Selecting the number of components in PCA using cross-validation approximations. Computational Statistics and Data Analysis.	pdf
2011	Josse, J., Husson, F. and Pagès, J.	Multiple imputation in PCA. Advances in data analysis and classification.	pdf
2010	Josse, J., Husson, F. and Pagès, J.	Principal component methods - hierarchical clustering - partitional clustering: why would we need to choose for visualizing data? Technical report.	pdf
2009	Josse, J., Husson, F. and Pagès, J.	Analyse en Composantes Principales. Journal de la SFdS.	pdf
2008	Josse, J., Husson, F. and Pagès, J.	Testing the significance of the RV coefficient. Computational Statistics and Data Analysis.	pdf
2008	Lê S., Josse, J. and Husson, F.	FactoMineR: an R package for multivariate analysis. Journal of Statistical Software.	pdf