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Reliable ABC model choice via random forests

Bioinformatics, 2016-03, Vol.32 (6), p.859-866

2016

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

Bioinformatics, 2014-04, Vol.30 (8), p.1187-1189

2014

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Estimation of population allele frequencies from next-generation sequencing data: pool-versus individual-based genotyping

Molecular ecology, 2013-07, Vol.22 (14), p.3766-3779

2013

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Bayesian computation via empirical likelihood

Proceedings of the National Academy of Sciences - PNAS, 2013-01, Vol.110 (4), p.1321-1326

2013

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Sympathetic axonal sprouting induces changes in macrophage populations and protects against pancreatic cancer

Nature communications, 2022-04, Vol.13 (1), p.1985-1985, Article 1985

2022

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Case Studies in Applied Bayesian Data Science: CIRM Jean-Morlet Chair, Fall 2018

1st Edition 2020, 2020

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Approximate Bayesian computational methods

Statistics and computing, 2012-11, Vol.22 (6), p.1167-1180

2012

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Bayesian Neural Networks: An Introduction and Survey

Case Studies in Applied Bayesian Data Science, p.45-87

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ABC random forests for Bayesian parameter inference

Bioinformatics, 2019-05, Vol.35 (10), p.1720-1728

2019

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Constraining the recent star formation history of galaxies: an approximate Bayesian computation approach

Astronomy and astrophysics (Berlin), 2020-03, Vol.635, p.A136

2020

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The effect of RAD allele dropout on the estimation of genetic variation within and between populations

Molecular ecology, 2013-06, Vol.22 (11), p.3165-3178

2013

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Deciphering the Routes of invasion of Drosophila suzukii by Means of ABC Random Forest

Molecular biology and evolution, 2017-04, Vol.34 (4), p.980-996

2017

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Consistency of adaptive importance sampling and recycling schemes

Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability, 2019-08, Vol.25 (3)

2019

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Consistency of the Adaptive Multiple Importance Sampling

Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability, 2019

2019

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Operator norm convergence of spectral clustering on level sets

Journal of machine learning research, 2011-02, Vol.12, p.385-416

2011

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Efficient learning in Approximate Bayesian Computation

Nature precedings, 2011-05

2011

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Maximum-likelihood inference of population size contractions from microsatellite data

Molecular biology and evolution, 2014-10, Vol.31 (10), p.2805-2823

2014

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Bayesian Functional Linear Regression with Sparse Step Functions

Bayesian analysis, 2019-03, Vol.14 (1), p.111-135

2019

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Adaptive ABC model choice and geometric summary statistics for hidden Gibbs random fields

Statistics and computing, 2015-01, Vol.25 (1), p.129-141

2015

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Estimation of demo-genetic model probabilities with Approximate Bayesian Computation using linear discriminant analysis on summary statistics

Molecular ecology resources, 2012-09, Vol.12 (5), p.846-855

2012

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Resampling: An improvement of importance sampling in varying population size models

Theoretical population biology, 2017-04, Vol.114, p.70-87

2017

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Outlier detection in non-stationary time series applied to sewer network monitoring

Internet of things (Amsterdam. Online), 2023-04, Vol.21, p.100654, Article 100654

2023

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The Normalized Graph Cut and Cheeger Constant: From Discrete to Continuous

Advances in applied probability, 2012-12, Vol.44 (4), p.907-937

2012

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Estimation of density level sets with a given probability content

Journal of nonparametric statistics, 2013-03, Vol.25 (1), p.261-272

2013

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Large deviations and full Edgeworth expansions for finite Markov chains with applications to the analysis of genomic sequences

Probability and statistics, 2010-01, Vol.14, p.435-455

Pudlo, Pierre

2010

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Reliable ABC model choice via random forests

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

Estimation of population allele frequencies from next-generation sequencing data: pool-versus individual-based genotyping

Bayesian computation via empirical likelihood

Sympathetic axonal sprouting induces changes in macrophage populations and protects against pancreatic cancer

Case Studies in Applied Bayesian Data Science: CIRM Jean-Morlet Chair, Fall 2018

Approximate Bayesian computational methods

Bayesian Neural Networks: An Introduction and Survey

ABC random forests for Bayesian parameter inference

Constraining the recent star formation history of galaxies: an approximate Bayesian computation approach

The effect of RAD allele dropout on the estimation of genetic variation within and between populations

Deciphering the Routes of invasion of Drosophila suzukii by Means of ABC Random Forest

Consistency of adaptive importance sampling and recycling schemes

Consistency of the Adaptive Multiple Importance Sampling

Operator norm convergence of spectral clustering on level sets

Efficient learning in Approximate Bayesian Computation

Maximum-likelihood inference of population size contractions from microsatellite data

Bayesian Functional Linear Regression with Sparse Step Functions

Adaptive ABC model choice and geometric summary statistics for hidden Gibbs random fields

Estimation of demo-genetic model probabilities with Approximate Bayesian Computation using linear discriminant analysis on summary statistics

Resampling: An improvement of importance sampling in varying population size models

Outlier detection in non-stationary time series applied to sewer network monitoring

The Normalized Graph Cut and Cheeger Constant: From Discrete to Continuous

Estimation of density level sets with a given probability content

Large deviations and full Edgeworth expansions for finite Markov chains with applications to the analysis of genomic sequences

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