Simon BARTHELME
Chargé de Recherche CNRS
Equipe Vision and Brain Signal Processing
Département Images et Signal
Chercheur CNRS
ME CONTACTER / CONTACT ME
Mail : simon.barthelme@gipsa-lab.grenoble-inp.fr

11 rue des mathématiques
Domaine Universitaire
BP 46
38402 Saint Martin d'Hères cedex

Bureau D1191
Tél.33 (0)4 76 82 64 22
Fax : 33 (0)4 76 57 47 90
PUBLICATIONS RECENTES / RECENT PUBLICATIONS
Les derniéres publications de la collection Gipsa dans HAL

Échantillonnage de signaux sur graphes via des processus déterminantaux

Nicolas Tremblay, Simon Barthelme, Pierre-Olivier Amblard. Échantillonnage de signaux sur graphes via des processus déterminantaux. GRETSI, Sep 2017, Juan-les-Pins, France. 〈hal-01503736v2〉

Graph sampling with determinantal processes

Nicolas Tremblay, Pierre-Olivier Amblard, Simon Barthelme. Graph sampling with determinantal processes. 2017. 〈hal-01483347〉

Bounding errors of Expectation-Propagation

Guillaume Dehaene, Simon Barthelme. Bounding errors of Expectation-Propagation. Neural Information Processing Systems (NIPS), Dec 2015, Montréal, Canada. 2015. 〈hal-01250082〉

Divide and conquer in ABC: Expectation-Progagation algorithms for likelihood-free inference

Simon Barthelme, Nicolas Chopin, Vincent Cottet. Divide and conquer in ABC: Expectation-Progagation algorithms for likelihood-free inference. To appear in the forthcoming Handbook of Approximate Bayesian Computation (ABC), edited by S. Sis.. 2015. 〈hal-01236876〉

The Poisson transform for unnormalised statistical models

Simon Barthelme, Nicolas Chopin. The Poisson transform for unnormalised statistical models. Statistics and Computing, Springer Verlag (Germany), 2015, 〈http://link.springer.com/article/10.1007/s11222-015-9559-4〉. 〈10.1007/s11222-015-9559-4〉. 〈hal-01235074〉

Expectation Propagation in the large-data limit

Guillaume Dehaene, Simon Barthelme. Expectation Propagation in the large-data limit. 2015. 〈hal-01235066〉

Fast matrix computations for functional additive models

Simon Barthelme. Fast matrix computations for functional additive models. Statistics and Computing, Springer Verlag (Germany), 2015, 〈10.1007/s11222-014-9490-0〉. 〈hal-01235072〉

ENCADREMENT DE THESES / PhD THESIS SUPERVISED

Grenoble Images Parole Signal Automatique laboratoire

UMR 5216 CNRS - Grenoble INP - Université Joseph Fourier - Université Stendhal