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Scaling Limits of Markov-Branching Trees and Applications

Lecture Notes of the XII Simposio de Probabilidad y Procesos Estocásticos 16–20 Novembre 2015, Mérida, Yucatán

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XII Symposium of Probability and Stochastic Processes

Part of the book series: Progress in Probability ((PRPR,volume 73))

Abstract

The goal of these lecture notes is to survey some of the recent progress on the description of large-scale structure of random trees. We use the framework of Markov-Branching sequences of trees and discuss several applications.

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Acknowledgements

I warmly thank the organizers of the XII Simposio de Probabilidad y Procesos Estocásticos, held in Mérida, as well as my collaborators on the topic of Markov-Branching trees, Grégory Miermont, Jim Pitman, Robin Stephenson and Matthias Winkel. Many thanks also to the referee for a very careful reading of a first version of this manuscript that led to many improvements in the presentation. This work was partially supported by the ANR GRAAL ANR–14–CE25–0014.

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  1. Université Paris 13, Sorbonne Paris Cité, LAGA, CNRS (UMR 7539), Villetaneuse, France

    Bénédicte Haas

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  1. Bénédicte Haas
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Editors and Affiliations

  1. Department of Probability and Statistics, Center for Research in Mathematics, Guanajuato, Mexico

    Daniel Hernández-Hernández

  2. Department of Probability and Statistics, Center for Research in Mathematics, Guanajuato, Mexico

    Juan Carlos Pardo

  3. Department of Probability and Statistics, Center for Research in Mathematics, Guanajuato, Mexico

    Victor Rivero

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Haas, B. (2018). Scaling Limits of Markov-Branching Trees and Applications. In: Hernández-Hernández, D., Pardo, J., Rivero, V. (eds) XII Symposium of Probability and Stochastic Processes. Progress in Probability, vol 73. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-77643-9_1

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