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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.

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

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

Map

 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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