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Phylogenetic networks provide a more general description of evolutionary relationships than rooted phylogenetic trees. One way to produce a phylogenetic network is to randomly place $k$ arcs between the edges of a rooted binary phylogenetic…

Populations and Evolution · Quantitative Biology 2025-03-19 Michael Fuchs , Mike Steel , Qiang Zhang

We consider Gibbs distributions on finite random plane trees with bounded branching. We show that as the order of the tree grows to infinity, the distribution of any finite neighborhood of the root of the tree converges to a limit. We…

Probability · Mathematics 2010-03-04 Yuri Bakhtin

We study a random recursive tree model featuring complete redirection called the random friend tree and introduced by Saram\"aki and Kaski. Vertices are attached in a sequential manner one by one by selecting an existing target vertex and…

A network growth mechanism based on a two-step preferential rule is investigated as a model of network growth in which no global knowledge of the network is required. In the first filtering step a subset of fixed size $m$ of existing nodes…

Disordered Systems and Neural Networks · Physics 2009-11-10 Hrvoje Stefancic , Vinko Zlatic

In this paper we present a generalized model for network growth that links the microscopical agent strategies with the large scale behavior. This model is intended to reproduce the largest number of features of the Internet network at the…

Statistical Mechanics · Physics 2007-05-23 Guido Caldarelli , Paolo De Los Rios , Luciano Pietronero

Interacting particle systems can often be constructed from a graphical representation, by applying local maps at the times of associated Poisson processes. This leads to a natural coupling of systems started in different initial states. We…

Probability · Mathematics 2020-03-19 Tibor Mach , Anja Sturm , Jan M. Swart

Tree structures are ubiquitous in data across many domains, and many datasets are naturally modelled by unobserved tree structures. In this paper, first we review the theory of random fragmentation processes [Bertoin, 2006], and a number of…

Machine Learning · Statistics 2015-09-17 Hong Ge , Yarin Gal , Zoubin Ghahramani

Random spanning trees are among the most prominent determinantal point processes. We give four examples of random spanning trees on ladder-like graphs whose rungs form stationary renewal processes or regenerative processes of order two,…

Probability · Mathematics 2017-04-04 Achim Klenke

Random Forest (Breiman, 2001) is a successful and widely used regression and classification algorithm. Part of its appeal and reason for its versatility is its (implicit) construction of a kernel-type weighting function on training data,…

Machine Learning · Statistics 2022-10-13 Domagoj Ćevid , Loris Michel , Jeffrey Näf , Nicolai Meinshausen , Peter Bühlmann

Given a solution to a recursive distributional equation, a natural (and non-trivial) question is whether the corresponding recursive tree process is endogenous. That is, whether the random environment almost surely defines the tree process.…

Probability · Mathematics 2016-10-25 Victor Kleptsyn , Michele Triestino

We introduce some natural families of distributions on rooted binary ranked plane trees with a view toward unifying ideas from various fields, including macroevolution, epidemiology, computational group theory, search algorithms and other…

Combinatorics · Mathematics 2017-08-22 Sean Cleary , Mareike Fischer , Robert C. Griffiths , Raazesh Sainudiin

In the critical beta-splitting model of a random $n$-leaf rooted tree, clades are recursively (from the root) split into sub-clades, and a clade of $m$ leaves is split into sub-clades containing $i$ and $m-i$ leaves with probabilities…

Probability · Mathematics 2025-04-21 David J. Aldous , Svante Janson

We consider the problem of the estimation of a high-dimensional probability distribution from i.i.d. samples of the distribution using model classes of functions in tree-based tensor formats, a particular case of tensor networks associated…

Machine Learning · Statistics 2021-05-21 Erwan Grelier , Anthony Nouy , Régis Lebrun

For a uniform random labelled tree, we find the limiting distribution of tree parameters which are stable (in some sense) with respect to local perturbations of the tree structure. The proof is based on the martingale central limit theorem…

Combinatorics · Mathematics 2022-06-16 Mikhail Isaev , Angus Southwell , Maksim Zhukovskii

A random intersection graph is constructed by assigning independently to each vertex a subset of a given set and drawing an edge between two vertices if and only if their respective subsets intersect. In this paper a model is developed in…

Probability · Mathematics 2015-09-24 Maria Deijfen , Willemien Kets

A common objective in the analysis of tabular data is estimating the conditional distribution (in contrast to only producing predictions) of a set of "outcome" variables given a set of "covariates", which is sometimes referred to as the…

Machine Learning · Statistics 2024-10-08 Zhuoqun Wang , Naoki Awaya , Li Ma

In this paper we model the tomography of scale free networks by studying the structure of layers around an arbitrary network node. We find, both analytically and empirically, that the distance distribution of all nodes from a specific…

Condensed Matter · Physics 2013-05-29 R. Cohen , D. Dolev , S. Havlin , T. Kalisky , O. Mokryn , Y. Shavitt

Raspaud and Wang conjectured that every triangle-free planar graph can be vertex-partitioned into an independent set and a forest. Independently, Kawarabayashi and Thomassen also remarked that this might be true, after providing another…

Combinatorics · Mathematics 2025-11-25 Guanwu Liu , Rongxing Xu

We derive the exact partition function for a discrete model of random trees embedded in a one-dimensional space. These trees have vertices labeled by integers representing their position in the target space, with the SOS constraint that…

Statistical Mechanics · Physics 2007-05-23 J. Bouttier , P. Di Francesco , E. Guitter

Random forests have become an established tool for classification and regression, in particular in high-dimensional settings and in the presence of complex predictor-response relationships. For bounded outcome variables restricted to the…

Methodology · Statistics 2019-01-21 Leonie Weinhold , Matthias Schmid , Marvin N. Wright , Moritz Berger