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20062023
most citedGeomstats: A Python Package for Riemannian Geometry in Machine Learning

96 citations · 178 across the 27 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

math.DG2019

Exploration of Balanced Metrics on Symmetric Positive Definite Matrices

Yann Thanwerdas, Xavier Pennec

Symmetric Positive Definite (SPD) matrices have been used in many fields of medical data analysis. Many Riemannian metrics have been defined on this manifold but the choice of the…

math.DG2019★ 13 cited

Curvature effects on the empirical mean in Riemannian and affine Manifolds: a non-asymptotic high concentration expansion in the small-sample regime

Xavier Pennec

The asymptotic concentration of the Fr{é}chet mean of IID random variables on a Rieman-nian manifold was established with a central limit theorem by Bhattacharya \& Patrangenaru (B…

cs.GR2019

Symmetric Algorithmic Components for Shape Analysis with Diffeomorphisms

N. Guigui, Shuman Jia, Maxime Sermesant +1

In computational anatomy, the statistical analysis of temporal deformations and inter-subject variability relies on shape registration. However, the numerical integration and optim…

math.DG2019★ 12 cited

Is affine invariance well defined on SPD matrices? A principled continuum of metrics

Yann Thanwerdas, Xavier Pennec

Symmetric Positive Definite (SPD) matrices have been widely used in medical data analysis and a number of different Riemannian met-rics were proposed to compute with them. However,…

q-bio.NC2019

A model of brain morphological changes related to aging and Alzheimer's disease from cross-sectional assessments

Raphaël Sivera, Hervé Delingette, Marco Lorenzi +2

In this study we propose a deformation-based framework to jointly model the influence of aging and Alzheimer's disease (AD) on the brain morphological evolution. Our approach combi…