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General theory for Big Bayes
In the modern era of complex and large data sets, there is stringent need for flexible, sound and scalable inferential methods to analyse them. Bayesian approaches have been increasingly used in statistics and machine learning and... In the modern era of complex and large data sets, there is stringent need for flexible, sound and scalable inferential methods to analyse them. Bayesian approaches have been increasingly used in statistics and machine learning and in all sorts of applications such as biostatistics, astrophysics, social science etc. Major advantages of Bayesian approaches are: their ability to model complex models in a hierarchical way, their coherency and ability to deliver not only point estimators but also measures of uncertainty from the posterior distribution which is a probability distribution on the parameter space at the core of all Bayesian inference. The increasing complexity of the data sets raise huge challenges for Bayesian approaches: theoretical and computational. The aim of this project is to develop a general theory for the analysis of Bayesian methods in complex and high (or infinite) dimensional models which will cover not only fine understanding of the posterior distributions but also an analysis of the output of the algorithms used to implement the approaches. The main objectives of the project are (briefly): 1. Asymptotic analysis of the posterior distribution of complex high dimensional models 2. Interactions between the asymptotic theory of high dimensional posterior distributions and computational complexity. We will also enrich these theoretical developments by 3 strongly related domains of applications, namely neuroscience, terrorism and crimes and ecology. ver más
31/03/2025
DAUPHINE
2M€
Duración del proyecto: 70 meses Fecha Inicio: 2019-05-10
Fecha Fin: 2025-03-31

Línea de financiación: concedida

El organismo H2020 notifico la concesión del proyecto el día 2019-05-10
Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:
ERC-2018-ADG: ERC Advanced Grant
Cerrada hace 6 años
Presupuesto El presupuesto total del proyecto asciende a 2M€
Líder del proyecto
UNIVERSITE PARIS DAUPHINE No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico TRL 4-5