A simple approximation method for the Fisher–Rao distance between multivariate normal distributions

F Nielsen - Entropy, 2023 - mdpi.com
We present a simple method to approximate the Fisher–Rao distance between multivariate
normal distributions based on discretizing curves joining normal distributions and …

Riemannian optimization for non-centered mixture of scaled Gaussian distributions

A Collas, A Breloy, C Ren, G Ginolhac… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This article studies the statistical model of the non-centered mixture of scaled Gaussian
distributions (NC-MSG). Using the Fisher-Rao information geometry associated with this …

The Fisher–Rao Geometry of CES Distributions

F Bouchard, A Breloy, A Collas, A Renaux… - … Distributions in Signal …, 2024 - Springer
When dealing with a parametric statistical model, a Riemannian manifold can naturally
appear by endowing the parameter space with the Fisher information metric. The geometry …

Géométrie riemannienne pour l'estimation et l'apprentissage statistiques: application à la télédétection

A Collas - 2022 - theses.hal.science
Remote sensing systems offer an increased opportunity to record multi-temporal and
multidimensional images of the earth's surface. This opportunity greatly increases the …

[PDF][PDF] Riemannian geometry for statistical estimation and learning: application to remote sensing

A Collas - 2022 - antoinecollas.fr
Remote sensing systems offer an increased opportunity to record multi-temporal and
multidimensional images of the earth's surface. This opportunity greatly increases the …

The Fisher-Rao Geometry of CES

F Bouchard, A Breloy, A Collas, A Renaux - … Symmetric Distributions in … - books.google.com
When dealing with a parametric statistical model, a Riemannian manifold can naturally
appear by endowing the parameter space with the Fisher information metric. The geometry …