output
20172023
most citedStatistical learning of spatiotemporal patterns from longitudinal manifold-valued networks

10 citations

6 papers

q-bio.QM20235 cited

The Smart Data Extractor, a Clinician Friendly Solution to Accelerate and Improve the Data Collection During Clinical Trials

Sophie Quennelle, Maxime Douillet, Lisa Friedlander +4

In medical research, the traditional way to collect data, i.e. browsing patient files, has been proven to induce bias, errors, human labor and costs. We propose a semi-automated sy…

stat.ML20231 cited

Variational Inference for Longitudinal Data Using Normalizing Flows

Clément Chadebec, Stéphanie Allassonnière

This paper introduces a new latent variable generative model able to handle high dimensional longitudinal data and relying on variational inference. The time dependency between the…

stat.ME20201 cited

Optimisation des parcours patients pour lutter contre l'errance de diagnostic des patients atteints de maladies rares

Frédéric Logé, Rémi Besson, Stéphanie Allassonnière

A patient suffering from a rare disease in France has to wait an average of two years before being diagnosed. This medical wandering is highly detrimental both for the health syste…

stat.ME20191 cited

Simulation of virtual cohorts increases predictive accuracy of cognitive decline in MCI subjects

Igor Koval, Stéphanie Allassonnière, Stanley Durrleman

The ability to predict the progression of biomarkers, notably in NDD, is limited by the size of the longitudinal data sets, in terms of number of patients, number of visits per pat…

stat.ML201710 cited

Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks

Igor Koval, Jean-Baptiste Schiratti, Alexandre Routier +4

We introduce a mixed-effects model to learn spatiotempo-ral patterns on a network by considering longitudinal measures distributed on a fixed graph. The data come from repeated obs…

math.ST20176 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…