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researcher / Nicolas Chopin

Nicolas Chopin

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Disciplines:

Applied mathematics

Chemistry

Cognitive sciences

Mathematics

Natural sciences

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Thesis:

Conception de ligands de type énaminone trifluorométhylée pour l’élaboration de complexes aux propriétés multiples

Applications des méthodes de Monte Carlo séquentielles à la statistique bayésienne

Directed Thesis:

Theoretical contributions to Monte Carlo methods, and applications to Statistics

High dimensional Bayesian computation

Computational learning noise in human decision-making

Theoretical study of some statistical procedures applied to complex data

Advances in computational Bayesian statistics and the approximation of Gibbs measures

Monte Carlo methods for sampling high-dimensional binary vectors