Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Duchamps Jean-Jil"'
Publikováno v:
ESAIM: Proceedings and Surveys, Vol 74, Pp 19-37 (2023)
The first talk at the session Random trees and random forests “Journée MAS” (27/08/2021) was presented by I. Kortchemski. After a general up-to-date introduction to local and scaling limits of Bienaymé trees (which are discrete branching trees)
Externí odkaz:
https://doaj.org/article/7cc7b41e308f41839f23e1473d2d760d
In recent years, there has been an effort to extend the classical notion of phylogenetic balance, originally defined in the context of trees, to networks. One of the most natural ways to do this is with the so-called $B_2$ index. In this paper, we st
Externí odkaz:
http://arxiv.org/abs/2407.19454
Autor:
Bienvenu, François, Duchamps, Jean-Jil
Publikováno v:
Electron. J. Probab. 29:1-48 (2024)
We introduce a biologically natural, mathematically tractable model of random phylogenetic network to describe evolution in the presence of hybridization. One of the features of this model is that the hybridization rate of the lineages correlates neg
Externí odkaz:
http://arxiv.org/abs/2211.02407
Autor:
Dombry, Clement, Duchamps, Jean-Jil
Infinitesimal gradient boosting (Dombry and Duchamps, 2021) is defined as the vanishing-learning-rate limit of the popular tree-based gradient boosting algorithm from machine learning. It is characterized as the solution of a nonlinear ordinary diffe
Externí odkaz:
http://arxiv.org/abs/2210.00736
We study a class of individual-based, fixed-population size epidemic models under general assumptions, e.g., heterogeneous contact rates encapsulating changes in behavior and/or enforcement of control measures. We show that the large-population dynam
Externí odkaz:
http://arxiv.org/abs/2106.13135
Autor:
Dombry, Clément, Duchamps, Jean-Jil
Publikováno v:
In Stochastic Processes and their Applications April 2024 170
Autor:
Dombry, Clément, Duchamps, Jean-Jil
We define infinitesimal gradient boosting as a limit of the popular tree-based gradient boosting algorithm from machine learning. The limit is considered in the vanishing-learning-rate asymptotic, that is when the learning rate tends to zero and the
Externí odkaz:
http://arxiv.org/abs/2104.13208
Autor:
Foutel-Rodier, Félix, Blanquart, François, Courau, Philibert, Czuppon, Peter, Duchamps, Jean-Jil, Gamblin, Jasmine, Kerdoncuff, Élise, Kulathinal, Rob, Régnier, Léo, Vuduc, Laura, Lambert, Amaury, Schertzer, Emmanuel
We present a unifying, tractable approach for studying the spread of viruses causing complex diseases requiring to be modeled using a large number of types (e.g., infective stage, clinical state, risk factor class). We show that recording each infect
Externí odkaz:
http://arxiv.org/abs/2007.09622
Autor:
Duchamps, Jean-Jil
We consider fragmentation processes with values in the space of marked partitions of $\mathbb{N}$, i.e. partitions where each block is decorated with a nonnegative real number. Assuming that the marks on distinct blocks evolve as independent positive
Externí odkaz:
http://arxiv.org/abs/1907.04712
Publikováno v:
Random Structures & Algorithms, 59(2):155-188 (2021)
Starting from any graph on $\{1, \ldots, n\}$, consider the Markov chain where at each time-step a uniformly chosen vertex is disconnected from all of its neighbors and reconnected to another uniformly chosen vertex. This Markov chain has a stationar
Externí odkaz:
http://arxiv.org/abs/1906.08806