7 citations
- Institut Universitaire de Recherche CliniqueFR3 papers
- Université de MontpellierFR3 papers
- Institut national de recherche en sciences et technologies du numériqueFR2 papers
- Biochimie des Protéines MembranairesFR1 paper
- Centre de Recherche Jean Pierre AubertFR1 paper
- Centre Hospitalier Universitaire de LilleFR1 paper
- Centre Hospitalier Universitaire de MontpellierFR1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Centre Oscar LambretFR1 paper
- Harvard UniversityUS1 paper
- Imperial College LondonGB1 paper
- InsermFR1 paper
6 papers · 1 filter
Do we Need Dozens of Methods for Real World Missing Value Imputation?
Krystyna Grzesiak, Christophe Muller, Julie Josse +1
Missing values pose a persistent challenge in modern data science. Consequently, there is an ever-growing number of publications introducing new imputation methods in various field…
When Pattern-by-Pattern Works: Theoretical and Empirical Insights for Logistic Models with Missing Values
Christophe Muller, Erwan Scornet, Julie Josse
Predicting with missing inputs challenges even parametric models, as parameter estimation alone is insufficient for prediction on incomplete data. While several works study predict…
Federated Learning for MRI-based BrainAGE: a multicenter study on post-stroke functional outcome prediction
Vincent Roca, Marc Tommasi, Paul Andrey +8
Brain-predicted age difference (BrainAGE) is a neuroimaging biomarker reflecting brain health. However, training robust BrainAGE models requires large dataset…
Optimal Transport with Heterogeneously Missing Data
Linus Bleistein, Aurélien Bellet, Julie Josse
We consider the problem of solving the optimal transport problem between two empirical distributions with missing values. Our main assumption is that the data is missing completely…
Model Agnostic Differentially Private Causal Inference
Christian Janos Lebeda, Mathieu Even, Aurélien Bellet +1
Estimating causal effects from observational data is essential in fields such as medicine, economics and social sciences, where privacy concerns are paramount. We propose a general…
Rethinking the Win Ratio: A Causal Framework for Hierarchical Outcome Analysis
Mathieu Even, Julie Josse
Quantifying causal effects in the presence of complex and multivariate outcomes remains a key challenge in treatment evaluation. For hierarchical multivariate outcomes, the FDA rec…