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Mesures de Feynman-Kac et Méthodes Particulaires

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Modèles et méthodes stochastiques

Part of the book series: Mathématiques et Applications ((MATHAPPLIC,volume 75))

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Résumé

La simulation de mesure de probabilités complexes sur des espaces de grandes dimensions est l’un des problèmes majeurs de l’ingénierie stochastique.

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References

  1. P. Drineas, R. Kannan, M.W. Mahoney. Fast Monte Carlo algorithms for matrices I: Approximating matrix multiplication. SIAM J. Comput. Vol. 36, No. 1, pp. 132–157 (2006).

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  2. P. Del Moral, L. Miclo. Genealogies and Increasing Propagations of Chaos for Feynman-Kac and Genetic Models. Annals of Applied Probability, vol. 11, No. 4, pp. 1166–1198 (2001).

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  3. P. Del Moral. Feynman-Kac formulae. Genealogical and interacting particle systems. Springer-Verlag: New York (2004).

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  4. Hara T. and Slade G. (1992), Self-avoiding walks in five or more dimensions: I. The critical behaviour. Communications in Mathematical Physics, 147, pp. 101–136.

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  5. S. Branford, C. Weihrauch and V. Alexandrov. A sparse parallel hybrid Monte Carlo algorithms for matrix computations, Proceedings of the 2005 International Conference on Computational Science, Eds.: V. Sunderam et al, Lecture Note in Computer Science,Vol. 3516, pp. 743-751 (2005).

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Correspondence to Pierre Del Moral .

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Del Moral, P., Vergé, C. (2014). Mesures de Feynman-Kac et Méthodes Particulaires. In: Modèles et méthodes stochastiques. Mathématiques et Applications, vol 75. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54616-7_8

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