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Let $M$ be a random matrix in the orthogonal group $\O_n$, distributed according to Haar measure, and let $A$ be a fixed $n\times n$ matrix over $\R$ such that $\tr(AA^t)=n$. Then the total variation distance of the random variable…

Probability · Mathematics 2010-05-18 Elizabeth Meckes

We prove that for any fixed $k$, the probability that a random vertex of a random increasing plane tree is of rank $k$, that is, the probability that a random vertex is at distance $k$ from the leaves, converges to a constant $c_k$ as the…

Combinatorics · Mathematics 2022-08-09 Miklós Bóna , Boris Pittel

Is there a constant $r_0$ such that, in any invariant tree network linking rate-$1$ Poisson points in the plane, the mean within-network distance between points at Euclidean distance $r$ is infinite for $r > r_0$? We prove a slightly weaker…

Probability · Mathematics 2021-03-02 David J. Aldous

There is great interest in predicting rare and extreme events in complex systems, and in particular, understanding the role of network topology in facilitating such events. In this work, we show that degree dispersion -- the fact that the…

Statistical Mechanics · Physics 2019-08-14 Jason Hindes , Michael Assaf

Let $G$ be a finite, simple connected graph. The average distance of a vertex $v$ of $G$ is the arithmetic mean of the distances from $v$ to all other vertices of $G$. The remoteness $\rho(G)$ of $G$ is the maximum of the average distances…

Combinatorics · Mathematics 2024-05-27 Peter Dankelmann , Sonwabile Mafunda , Sufiyan Mallu

Network complexity has been studied for over half a century and has found a wide range of applications. Many methods have been developed to characterize and estimate the complexity of networks. However, there has been little research with…

Machine Learning · Statistics 2021-01-13 Yann Issartel

Consider the Erd\H{o}s-Renyi random graph on n vertices where each edge is present independently with probability c/n, with c>0 fixed. For large n, a typical random graph locally behaves like a Galton-Watson tree with Poisson offspring…

Probability · Mathematics 2016-04-08 Charles Bordenave , Pietro Caputo

Arboreal networks are a generalization of rooted trees, defined by keeping the tree-like structure, but dropping the requirement for a single root. Just as the class of cographs is precisely the class of undirected graphs that can be…

Combinatorics · Mathematics 2025-02-13 Guillaume E. Scholz

We analyze a class of spatial random spanning trees built on a realization of a homogeneous Poisson point process of the plane. This tree has a simple radial structure with the origin as its root. We first use stochastic geometry arguments…

Probability · Mathematics 2007-05-23 Francois Baccelli , Charles Bordenave

We present analytical results for the distribution of shortest path lengths between random pairs of nodes in configuration model networks. The results, which are based on recursion equations, are shown to be in good agreement with numerical…

Disordered Systems and Neural Networks · Physics 2016-06-16 Mor Nitzan , Eytan Katzav , Reimer Kühn , Ofer Biham

We analyze complexity in spatial network ensembles through the lens of graph entropy. Mathematically, we model a spatial network as a soft random geometric graph, i.e., a graph with two sources of randomness, namely nodes located randomly…

Physics and Society · Physics 2018-05-02 Justin P. Coon , Carl P. Dettmann , Orestis Georgiou

Let $r$ and $d$ be positive integers with $r<d$. Consider a random $d$-ary tree constructed as follows. Start with a single vertex, and in each time-step choose a uniformly random leaf and give it $d$ newly created offspring. Let ${\mathcal…

Probability · Mathematics 2014-04-15 Andrea Collevecchio , Abbas Mehrabian , Nick Wormald

We develop a theory to measure the variance and covariance of probability distributions defined on the nodes of a graph, which takes into account the distance between nodes. Our approach generalizes the usual (co)variance to the setting of…

Physics and Society · Physics 2021-08-19 Karel Devriendt , Samuel Martin-Gutierrez , Renaud Lambiotte

Phylogenetic networks extend phylogenetic trees to model non-vertical inheritance, by which a lineage inherits material from multiple parents. The computational complexity of estimating phylogenetic networks from genome-wide data with…

Populations and Evolution · Quantitative Biology 2022-06-28 Jingcheng Xu , Cécile Ané

Ranked tree-child networks are a recently introduced class of rooted phylogenetic networks in which the evolutionary events represented by the network are ordered so as to respect the flow of time. This class includes the well-studied…

Populations and Evolution · Quantitative Biology 2024-10-15 Vincent Moulton , Andreas Spillner

Distance plays a fundamental role in measuring similarity between objects. Various visualization techniques and learning tasks in statistics and machine learning such as shape matching, classification, dimension reduction and clustering…

Machine Learning · Statistics 2025-04-23 Dianbin Bao , Kisung You , Lizhen Lin

We study spatial embeddings of random graphs in which nodes are randomly distributed in geographical space. We let the edge probability between any two nodes to be dependent on the spatial distance between them and demonstrate that this…

Physics and Society · Physics 2009-11-11 Ling Heng Wong , Philippa Pattison , Garry Robins

For $d\ge 2$ and an odd prime power $q$, consider the vector space $\mathbb{F}_q^d$ over the finite field $\mathbb{F}_q$, where the distance between two points $(x_1,\ldots,x_d)$ and $(y_1,\ldots,y_d)$ is defined as $\sum_{i=1}^d…

Combinatorics · Mathematics 2024-03-14 Debsoumya Chakraborti , Ben Lund

The family of planar graphs is a particularly important family and models many real-world networks. In this paper, we propose a principled framework based on the widely-known Apollonian packing process to generate new planar network, i.e.,…

Physics and Society · Physics 2023-12-27 Fei Ma , Jinzhi Ouyang , Ping Wang , Haobin Shi , Wei Pan

Generative Adversarial Networks (GANs) have achieved a great success in unsupervised learning. Despite its remarkable empirical performance, there are limited theoretical studies on the statistical properties of GANs. This paper provides…

Machine Learning · Computer Science 2022-07-22 Minshuo Chen , Wenjing Liao , Hongyuan Zha , Tuo Zhao
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