Jean-Michel Marin

According to our database, Jean-Michel Marin authored at least 17 papers between 2006 and 2019.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2019

ABC random forests for Bayesian parameter inference.

Louis Raynal, Jean-Michel Marin, Pierre Pudlo, Mathieu Ribatet, Christian P. Robert, Arnaud Estoup

Bioinform., 2019

2018

Probing instructions for expression regulation in gene nucleotide compositions.

Chloé Bessière, May Taha, Florent Petitprez, Jimmy Vandel, Jean-Michel Marin, Laurent Bréhélin, Sophie Lèbre, Charles-Henri Lecellier

PLoS Comput. Biol., 2018

2016

Reliable ABC model choice via random forests.

Pierre Pudlo, Jean-Michel Marin, Arnaud Estoup, Jean-Marie Cornuet, Mathieu Gautier, Christian P. Robert

Bioinform., 2016

2014

Bounding rare event probabilities in computer experiments.

Yves Auffray, Pierre Barbillon, Jean-Michel Marin

Comput. Stat. Data Anal., 2014

DIYABC v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data.

Jean-Marie Cornuet, Pierre Pudlo, Julien Veyssier, Alexandre Dehne-Garcia, Mathieu Gautier, Raphaël Leblois, Jean-Michel Marin, Arnaud Estoup

Bioinform., 2014

2012

Approximate Bayesian computational methods.

Jean-Michel Marin, Pierre Pudlo, Christian P. Robert, Robin J. Ryder

Stat. Comput., 2012

An empirical Bayes procedure for the selection of Gaussian graphical models.

Sophie Donnet, Jean-Michel Marin

Stat. Comput., 2012

Maximin design on non hypercube domains and kernel interpolation.

Yves Auffray, Pierre Barbillon, Jean-Michel Marin

Stat. Comput., 2012

Optimal parallelization of a sequential approximate Bayesian computation algorithm.

Jean-Michel Marin, Pierre Pudlo, Mohammed Sedki

Proceedings of the Winter Simulation Conference, 2012

2010

Discounting and divergence of opinion.

Elyès Jouini, Jean-Michel Marin, Clotilde Napp

J. Econ. Theory, 2010

On variance stabilisation in Population Monte Carlo by double Rao-Blackwellisation.

Alessandra Iacobucci, Jean-Michel Marin, Christian P. Robert

Comput. Stat. Data Anal., 2010

2008

Adaptive importance sampling in general mixture classes.

Olivier Cappé, Randal Douc, Arnaud Guillin, Jean-Michel Marin, Christian P. Robert

Stat. Comput., 2008

Inferring population history with <i>DIY ABC</i>: a user-friendly approach to approximate Bayesian computation.

Jean-Marie Cornuet, Filipe Santos, Mark A. Beaumont, Christian P. Robert, Jean-Michel Marin, David J. Balding, Thomas Guillemaud, Arnaud Estoup

Bioinform., 2008

2007

Confidence bands for Brownian motion and applications to Monte Carlo simulation.

Wilfrid S. Kendall, Jean-Michel Marin, Christian P. Robert

Stat. Comput., 2007

Initiation à R.

Romain François, Jean-Michel Marin

Monde des Util. Anal. Données, 2007

Mean-field variational approximate Bayesian inference for latent variable models.

Guido Consonni, Jean-Michel Marin

Comput. Stat. Data Anal., 2007

2006

Iterated importance sampling in missing data problems.

Gilles Celeux, Jean-Michel Marin, Christian P. Robert

Comput. Stat. Data Anal., 2006