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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.

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

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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