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Yann Cabanes

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CG1
  • cs.LG1
  • eess.SP1

identity via Semantic Scholar / OpenAlex

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

96 citations · 96 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CG2021

ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results

Nina Miolane, Matteo Caorsi, Umberto Lupo +30

This paper presents the computational challenge on differential geometry and topology that happened within the ICLR 2021 workshop "Geometric and Topological Representation Learning…

eess.SP2020

The Basic Geometric Structures of Electromagnetic Digital Information: Statistical characterization of the digital measurement of spatio-Doppler and polarimetric fluctuations of the radar electromagnetic wave

Frédéric Barbaresco, Yann Cabanes

The aim is to describe new geometric approaches to define the statistics of spatio-temporal and polarimetric measurements of the states of an electromagnetic wave, using the works…

cs.LG2020★ 96 cited

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.