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G-Statistics SIGNED

Foundations of Geometric Statistics and Their Application in the Life Sciences

Total Cost €

0

EC-Contrib. €

0

Partnership

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 G-Statistics project word cloud

Explore the words cloud of the G-Statistics project. It provides you a very rough idea of what is the project "G-Statistics" about.

radically    requiring    linear    encode    methodology    invariance    approximate    subspaces    curvature    affine    images    dimension    negatively    statistical    provides    sciences    diverges    singularities    specializations    unify    estimation    computational    emphasis    poincar    discipline    hierarchically    shapes    naturally    geometry    crossing    object    laws    establishing    quotient    stratification    structure    euclidean    databases    surveying    curved    foundations    theorems    geometric    algorithms    explaining    medical    ways    mathematics    anatomical    connection    anatomy    estimate    stratified    estimations    convenient    arise    manifolds    appear    metric    data    gauge    forecasting    power    illustrating    groups    physics    tools    efficient    approximation    mainly    theories    life    unreasonable    principled    flags    put    true    structures    transformation    exemplifying    effectiveness    inventing    lie    spaces    statisticians    evolution    riemannian    rephrasing    eacute    explore    statistics    mathematical    natural    illustrate   

Project "G-Statistics" data sheet

The following table provides information about the project.

Coordinator
INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE 

Organization address
address: DOMAINE DE VOLUCEAU ROCQUENCOURT
city: LE CHESNAY CEDEX
postcode: 78153
website: www.inria.fr

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country France [FR]
 Total cost 2˙183˙583 €
 EC max contribution 2˙183˙583 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2017-ADG
 Funding Scheme ERC-ADG
 Starting year 2018
 Duration (year-month-day) from 2018-09-01   to  2023-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE FR (LE CHESNAY CEDEX) coordinator 2˙183˙583.00

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 Project objective

'Invariance under gauge transformation groups provides the natural structure explaining the laws of physics. In life sciences, new mathematical tools are needed to estimate approximate invariance and establish general but approximate laws. Rephrasing Poincaré: a geometry cannot be more true than another, it may just be more convenient, and statisticians must find the most convenient one for their data. At the crossing of geometry and statistics, G-Statistics aims at establishing the mathematical foundations of geometric statistics and exemplifying their impact on selected applications in the life sciences.

So far, mainly Riemannian manifolds and negatively curved metric spaces have been studied. Other geometric structures like quotient spaces, stratified spaces or affine connection spaces naturally arise in applications. G-Statistics will explore ways to unify statistical estimation theories, explaining how the statistical estimations diverges from the Euclidean case in the presence of curvature, singularities, stratification. Beyond classical manifolds, particular emphasis will be put on flags of subspaces in manifolds as they appear to be natural mathematical object to encode hierarchically embedded approximation spaces.

In order to establish geometric statistics as an effective discipline, G-Statistics will propose new mathematical structures and theorems to characterize their properties. It will also implement novel generic algorithms and illustrate the impact of some of their efficient specializations on selected applications in life sciences. Surveying the manifolds of anatomical shapes and forecasting their evolution from databases of medical images is a key problem in computational anatomy requiring dimension reduction in non-linear spaces and Lie groups. By inventing radically new principled estimations methods, we aim at illustrating the power of the methodology and strengthening the 'unreasonable effectiveness of mathematics' for life sciences.'

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The information about "G-STATISTICS" are provided by the European Opendata Portal: CORDIS opendata.

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