96 citations · 99 across the 3 of their papers we have counts for
6 papers
Parametric information geometry with the package Geomstats
Alice Le Brigant, Jules Deschamps, Antoine Collas +1
We introduce the information geometry module of the Python package Geomstats. The module first implements Fisher-Rao Riemannian manifolds of widely used parametric families of prob…
Geomstats: A Python Package for Riemannian Geometry in Machine Learning
Nina Miolane, Alice Le Brigant, Johan Mathe +16
We introduce Geomstats, an open-source Python toolbox for computations and statistics on nonlinear manifolds, such as hyperbolic spaces, spaces of symmetric positive definite matri…
Intrinsic Riemannian metrics on spaces of curves: theory and computation
Martin Bauer, Nicolas Charon, Eric Klassen +1
This chapter reviews some past and recent developments in shape comparison and analysis of curves based on the computation of intrinsic Riemannian metrics on the space of curves mo…
The Fisher-Rao geometry of beta distributions applied to the study of canonical moments
Alice Le Brigant, Stéphane Puechmorel
This paper studies the Fisher-Rao geometry on the parameter space of beta distributions. We derive the geodesic equations and the sectional curvature, and prove that it is negative…
Math in the Black Forest: Workshop on New Directions in Shape Analysis
Martin Bauer, Nicolas Charon, Philipp Harms +9
These are the proceedings of the workshop "Math in the Black Forest", which brought together researchers in shape analysis to discuss promising new directions. Shape analysis is an…
Optimal Riemannian quantization with an application to air traffic analysis
Alice Le Brigant, Stéphane Puechmorel
The goal of optimal quantization is to find the best approximation of a probability distribution by a discrete measure with finite support. When dealing with empirical distribution…