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authIdHal_s : jean-michel-marin
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Detection of loci under selection from temporal population genomic data through ABC random forest

Vitor Pavinato , Jean-Michel Marin , Miguel Navascués
7. journées scientifiques du LabEx NUMEV, Nov 2018, Montpellier, France. , 2018
Poster communications hal-02787307v1
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Adaptive Importance Sampling in General Mixture Classes

Olivier Cappé , Randal Douc , Arnaud Guillin , Jean-Michel Marin , Christian P. Robert
[Research Report] RR-6332, INRIA. 2008
Reports inria-00181474v4
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Brownian Confidence Bands on Monte Carlo Output

W.S. Kendall , Jean-Michel Marin , C.P. Robert
Statistics and Computing, 2007, 17 (1), pp.1-10
Journal articles inria-00070571v1
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Probing instructions for expression regulation in gene nucleotide compositions

Chloé Bessière , May Taha , Florent Petitprez , Jimmy Vandel , Jean-Michel Marin , et al.
PLoS Computational Biology, 2018, 14 (1), pp.e1005921. ⟨10.1371/journal.pcbi.1005921⟩
Journal articles lirmm-01744469v1
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Modélisation de l'expression des gènes à partir de données de séquence ADN

May Taha , Chloé Bessière , Florent Petitprez , Jimmy Vandel , Jean-Michel Marin , et al.
JdS 2017, 49èmes Journées de Statistique de la SFdS, May 2017, Avignon, France
Conference papers hal-02068289v1

Computational Solutions for Bayesian Inference in Mixture Models

Christian Robert , Gilles Celeux , Kaniav Kamary , Gertraud Malsiner-Walli , Jean-Michel Marin
Handbook of Mixture Analysis, CRC Press, 2018
Book sections hal-01961038v1

Relevant statistics for Bayesian model choice

Jean-Michel Marin , Natesh S. Pillai , Christian P. Robert , Judith Rousseau
Journal of the Royal Statistical Society: Series B, 2014, 76 (5), pp.1-25. ⟨10.1111/rssb.12056⟩
Journal articles hal-01067901v1
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A Bayesian reassessment of nearest-neighbour classification

Lionel Cucala , Jean-Michel Marin , Christian Robert , Mike Titterington
Journal of the American Statistical Association, 2009, 104 (485), pp.263-273. ⟨10.1198/jasa.2009.0125⟩
Journal articles inria-00143783v4

Linear Toeplitz covariance structure models with optimal estimators of variance components

Jean-Michel Marin , Thierry Dhorne
Linear Algebra and its Applications, 2002, 354 (1-3), pp.195-212
Journal articles hal-01337417v1

Approximate Bayesian computational methods

Jean-Michel Marin , Pierre Pudlo , Christian P. Robert , Robin Ryder
Statistics and Computing, 2012, 22 (6), ⟨10.1007/s11222-011-9288-2⟩
Journal articles hal-00567240v2

Approximate Bayesian Computation using Random Forest

Jean-Michel Marin , Pierre Pudlo , Louis Raynal , Arnaud A Estoup , Christian P. Robert
Validating and Expanding Approximate Bayesian Computation Methods (17w5025), Banff International Research Station for Mathematical Innovation and Discovery (BIRS). MEX., Feb 2017, Banff, Canada
Conference papers hal-02786888v1

Discussions on "Riemann manifold Langevin and Hamiltonian Monte Carlo methods

Simon Barthelme , Magali Beffy , Nicolas Chopin , Arnaud Doucet , Pierre Jacob , et al.
Preprints, Working Papers, ... hal-00596301v1

Estimation of rare events probabilities in computer experiments

Yves Auffray , Pierre Barbillon , Jean-Michel Marin
Preprints, Working Papers, ... inria-00638696v1

Bayesian Inference on a Mixture Model With Spatial Dependence

Lionel Cucala , Jean-Michel Marin
Journal of Computational and Graphical Statistics, 2013, 22 (3), ⟨10.1080/10618600.2013.805652⟩
Journal articles hal-00793844v1
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On variance stabilisation in Population Monte Carlo by double Rao-Blackwellisation

Alessandra Iacobucci , Jean-Michel Marin , Christian P. Robert
Computational Statistics and Data Analysis, 2010, 54 (3), pp.698-710. ⟨10.1016/j.csda.2008.09.020⟩
Journal articles inria-00260141v1

Consistency of the Adaptive Multiple Importance Sampling

Jean-Michel Marin , Pierre Pudlo , Mohammed Sedki
Bernoulli, 2019, ⟨10.3150/18-BEJ1042⟩
Journal articles hal-01337195v1

Bounding rare event probabilities in computer experiments

Pierre Barbillon , Yves Auffray , Jean-Michel Marin
Uncertainty in computer models 2012 Conference, Jul 2012, Sheffield, United Kingdom
Conference papers hal-01587031v1

Infering population history with DIY ABC: a user-friendly approach to Approximate Bayesian Computation.

Jean-Marie Cornuet , Filipe Santos , Marc A. Beaumont , Christian Robert , Jean-Michel Marin , et al.
Bioinformatics, 2008, 24 (23), pp.2713-2719. ⟨10.1093/bioinformatics/btn514⟩
Journal articles hal-00359624v1

Are risk averse agents more optimistic ?

Selima Benmansour , Elyès Jouini , Jean-Michel Marin , Clotilde Napp , Christian P. Robert
EGRIE, 2006, Barcelone, Spain
Conference papers halshs-00163619v1
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Are risk averse agents more optimistic? A Bayesian estimation approach

Selima Benmansour , Elyès Jouini , Clotilde Napp , Jean-Michel Marin , Christian P. Robert
Preprints, Working Papers, ... halshs-00163678v1

Convergence of adaptive mixtures of importance sampling schemes

R. Douc , A. Guillin , Jean-Michel Marin , C. P. Robert
Statistics and Computing, 2008, 18,, pp.447-459
Journal articles hal-00432955v1
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Bringing ABC inference to the machine learning realm : AbcRanger, an optimized random forests library for ABC

François-David Collin , Arnaud Estoup , Jean-Michel Marin , Louis Raynal
JOBIM 2020, Jun 2020, Montpellier, France
Conference papers hal-02910067v2

Efficient learning in ABC algorithms

Mohammed Sedki , Jean-Marie Cornuet , Jean-Michel Marin , Pierre Pudlo , Christian P. Robert
Preprints, Working Papers, ... hal-00741572v1

Some discussions on the Read Paper "Beyond subjective and objective in statistics" by A. Gelman and C. Hennig

Christian Robert , Gilles Celeux , Jack Jewson , Julie Josse , Jean-Michel Marin , et al.
Preprints, Working Papers, ... hal-01968779v1

ABC random forests for Bayesian parameter inference

Louis Raynal , Jean-Michel Marin , Pierre Pudlo , Mathieu Ribatet , Christian Robert , et al.
Bioinformatics, 2019, 35 (10), pp.1720-1728. ⟨10.1093/bioinformatics/bty867⟩
Journal articles hal-01337189v2

On Particle Learning

Nicolas Chopin , Alessandra Iacobucci , Jean-Michel Marin , Kerrie Mengersen , Christian Robert , et al.
Preprints, Working Papers, ... hal-00494357v1

Some discussions of D. Fearnhead and D. Prangle's Read Paper "Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation

Christophe Andrieu , Simon Barthelme , Nicolas Chopin , Julien Cornebise , Arnaud Doucet , et al.
Preprints, Working Papers, ... hal-00658084v1

Detecting past contraction in population size using runs of homozygosity

Coralie Merle , Raphaël Leblois , Jean-Michel Marin , François Rousset
48èmes Journées de Statistique de la SFdS, May 2016, Montpellier, France
Conference papers hal-02932426v1

ABC methods for model choice in Gibbs random fields

Aude Grelaud , Christian Robert , Jean-Michel Marin
Comptes Rendus. Mathématique, 2009, 347 (3-4), pp.205-210. ⟨10.1016/j.crma.2008.12.009⟩
Journal articles hal-00450730v1

On computational tools for Bayesian data analysis

Christian Robert , Jean-Michel Marin
Preprints, Working Papers, ... hal-00473020v1