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NEO: Non Equilibrium Sampling on the Orbit of a Deterministic Transform35th International Conference on Neural Information Processing Systems, Dec 2021, Online, France. ⟨10.5555/3540261.3541565⟩
Communication dans un congrès
hal-03168489v2
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Approximate Bayesian Computation using Random ForestValidating and Expanding Approximate Bayesian Computation Methods (17w5025), Banff International Research Station for Mathematical Innovation and Discovery (BIRS). MEX., Feb 2017, Banff, Canada
Communication dans un congrès
hal-02786888v1
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Jeffreys’ Priors for Mixture EstimationBayesian Statistics from Methods to Models and Applications / BAYSM 2014, Sep 2014, Vienna, Austria. pp.37-48, ⟨10.1007/978-3-319-16238-6_4⟩
Communication dans un congrès
hal-01276489v1
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Empirical likelihood for Bayesian inference in population geneticsMathematical and Computational Evolutionnary Biology 2012, Jun 2012, Montpellier, France
Communication dans un congrès
hal-02932407v1
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Modélisation bayésienne hiérarchique pour l'estimation de matrice de covariance - Application à la gestion actif-passif de portefeuilles financiers42èmes Journées de Statistique, 2010, Marseille, France, France
Communication dans un congrès
inria-00494745v1
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Optimisation de plans d'expérience par méthodes particulaires35. Journées de Statistiques, Jun 2003, Lyon, France. pp.97-100
Communication dans un congrès
ineris-00972424v1
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Handbook of Mixture AnalysisTaylor & Francis, 2019
Ouvrages
hal-03943314v1
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Handbook of Mixture AnalysisCRC Press, pp.1-536, 2018, Chapman & Hall/CRC Handbooks of Modern Statistical Methods, 9781498763813
Ouvrages
hal-01928103v1
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Bayesian essentials with RSpringer Verlag, New York, pp.XIV-296, 2014, Springer Textbooks in Statistics, 978-1-4614-8686-2
Ouvrages
hal-01337395v1
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Introducing Monte Carlo Methods with RRobert Gentleman. Springer Verlag, New York, pp.284, 2009, Use R, John Kimmel, ⟨10.1007/1441915753⟩
Ouvrages
hal-00450502v1
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Bayesian Core: A practical approach to computational Bayesian statisticsSpringer Verlag, New York, pp.258, 2007, Springer Textbooks in Statistics, ⟨10.1007/978-0-387-38983-7⟩
Ouvrages
hal-00450489v1
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Approximate Bayesian computation, an introductionJean-Baptiste Marquette Didier Fraix‐Burnet Stéphane Girard and Julyan Arbel. Statistics for Astrophysics, EDP Sciences, pp.77-112, 2021, 978-2-7598-2275-1. ⟨10.1051/978-2-7598-2275-1.c008⟩
Chapitre d'ouvrage
hal-03912165v1
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A Bayesian Generalized Poisson Model for Cyber Risk AnalysisMathematical and Statistical Methods for Actuarial Sciences and Finance, Springer International Publishing; Springer International Publishing, pp.123-128, 2021, ⟨10.1007/978-3-030-78965-7_19⟩
Chapitre d'ouvrage
hal-03523624v1
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Markov Chain Monte Carlo Algorithms for Bayesian Computation, a Survey and Some GeneralisationCase Studies in Applied Bayesian Data Science, 2259, Springer International Publishing, pp.89-119, 2020, Lecture Notes in Mathematics, ⟨10.1007/978-3-030-42553-1_4⟩
Chapitre d'ouvrage
hal-03912194v1
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Application of ABC to Infer the Genetic History of Pygmy Hunter-Gatherer Populations from Western Central AfricaScott A. Sisson; Yanan Fan; Mark A. Beaumont. Handbook of Approximate Bayesian Computation, Chapman and Hall, Chapter 18, 2019, Chapman & Hall/CRC Handbooks of Modern Statistical Methods, 9781439881507
Chapitre d'ouvrage
hal-02787321v1
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Model Selection for Mixture Models-Perspectives and StrategiesHandbook of Mixture Analysis, CRC Press, 2018
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hal-01961077v1
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Computational Solutions for Bayesian Inference in Mixture ModelsHandbook of Mixture Analysis, CRC Press, 2018
Chapitre d'ouvrage
hal-01961038v1
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Approximate Bayesian Computation: A Survey on Recent ResultsRonald Cools; Dirk Nuyens. Monte Carlo and Quasi-Monte Carlo Methods, Springer International Publishing, pp.185-205, 2016, 978-3-319-33505-6. ⟨10.1007/978-3-319-33507-0_7⟩
Chapitre d'ouvrage
hal-01409281v1
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Bayesian Inference and computationD. Balding, M. Stumpf, M. Girolami. Handbook of Statistical Systems Biology, John Wiley, pp.39-65, 2011, 978-0-470-71086-9
Chapitre d'ouvrage
hal-00473021v1
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Importance sampling methods for Bayesian discrimination between embedded modelsM.-H. Chen, D. Dey, P. Mueller, D. Sun and K. Ye. Frontiers of Statistical Decision Making and Bayesian Analysis, Springer-Verlag, New York, pp.513-527, 2010
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