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20072023
most citedData Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder

103 citations · 187 across the 20 of their papers we have counts for

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6 papers · 1 filter

math.ST2020

Mixture of Conditional Gaussian Graphical Models for unlabelled heterogeneous populations in the presence of co-factors

Thomas Lartigue, Stanley Durrleman, Stéphanie Allassonnière

Conditional correlation networks, within Gaussian Graphical Models (GGM), are widely used to describe the direct interactions between the components of a random vector. In the case…

math.ST2020★ 9 cited

Deterministic Approximate EM Algorithm; Application to the Riemann Approximation EM and the Tempered EM

Thomas Lartigue, Stanley Durrleman, Stéphanie Allassonnière

The Expectation Maximisation (EM) algorithm is widely used to optimise non-convex likelihood functions with latent variables. Many authors modified its simple design to fit more sp…

math.ST2017★ 6 cited

Inconsistency of Template Estimation by Minimizing of the Variance/Pre-Variance in the Quotient Space

Loïc Devilliers, Stéphanie Allassonnière, Alain Trouvé +1

We tackle the problem of template estimation when data have been randomly deformed under a group action in the presence of noise. In order to estimate the template, one often minim…

math.ST2017

Inconsistency of Template Estimation with the Fr{é}chet mean in Quotient Space

Loïc Devilliers, Xavier Pennec, Stéphanie Allassonnière

We tackle the problem of template estimation when data have been randomly transformed under an isometric group action in the presence of noise. In order to estimate the template, o…

math.ST2016

Template estimation in computational anatomy: Fréchet means in top and quotient spaces are not consistent

Loïc Devilliers, Stéphanie Allassonnière, Alain Trouvé +1

In this article, we study the consistency of the template estimation with the Fréchet mean in quotient spaces. The Fréchet mean in quotient spaces is often used when the observatio…

math.ST2012

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…