3 citations · 11 across the 11 of their papers we have counts for
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Estimation and variable selection in high dimension in nonlinear mixed-effects models
Antoine Caillebotte, Estelle Kuhn, Sarah Lemler
We consider nonlinear mixed effects models including high-dimensional covariates to model individual parameters variability. The objective is to identify relevant covariates among…
Efficient preconditioned stochastic gradient descent for estimation in latent variable models
Charlotte Baey, Maud Delattre, Estelle Kuhn +2
Latent variable models are powerful tools for modeling complex phenomena involving in particular partially observed data, unobserved variables or underlying complex unknown structu…
Estimation and variable selection in high dimension in a causal joint model of survival times and longitudinal outcomes with random effects
Antoine Caillebotte, Estelle Kuhn, Sarah Lemler
We consider a joint survival and mixed-effects model to explain the survival time from longitudinal data and high-dimensional covariates in a population. The longitudinal data is m…
Convergent Stochastic Expectation Maximization algorithm with efficient sampling in high dimension. Application to deformable template model estimation
Stéphanie Allassonniere, Estelle Kuhn
Estimation in the deformable template model is a big challenge in image analysis. The issue is to estimate an atlas of a population. This atlas contains a template and the correspo…