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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.

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

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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