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This paper contains results relating currents and voltages in resistive networks to appropriate random trees or forests in those networks.

Probability · Mathematics 2012-01-17 Hariharan Narayanan

This paper considers limit theorems associated with subgraph counts in the age-dependent random connection model. First, we identify regimes where the count of sub-trees converges weakly to a stable random variable under suitable…

Probability · Mathematics 2024-09-10 Christian Hirsch , Takashi Owada

Directed acyclic graphs are a fundamental class of networks that includes citation networks, food webs, and family trees, among others. Here we define a random graph model for directed acyclic graphs and give solutions for a number of the…

Physics and Society · Physics 2009-03-23 Brian Karrer , M. E. J. Newman

We study the statistical properties of the sampled networks by a random walker. We compare topological properties of the sampled networks such as degree distribution, degree-degree correlation, and clustering coefficient with those of the…

Physics and Society · Physics 2009-11-13 Sooyeon Yoon , Sungmin Lee , Soon-Hyung Yook , Yup Kim

Tree-child networks are an important class of phylogenetic network used to model reticulate evolutionary processes. These networks have attracted increasing attention from researchers with interests in both combinatorics and algorithms. A…

Combinatorics · Mathematics 2026-05-11 Hexuan Liu , Michael Wallner , Guan-Ru Yu

We study normal approximation of subgraph counts in a model of spatial scale-free random networks known as the age-dependent random connection model. In the light-tailed regime where only moments of order $(2 + \varepsilon)$ are finite, we…

Probability · Mathematics 2025-05-15 Christian Hirsch , Raphaël Lachièze-Rey , Takashi Owada

In random graph models, the degree distribution of an individual node should be distinguished from the (empirical) degree distribution of the graph that records the fractions of nodes with given degree. We introduce a general framework to…

Social and Information Networks · Computer Science 2018-11-14 Siddharth Pal , Armand M. Makowski

Daily internet communication relies heavily on tree-structured graphs, embodied by popular data formats such as XML and JSON. However, many recent generative (probabilistic) models utilize neural networks to learn a probability distribution…

Machine Learning · Computer Science 2024-08-20 Milan Papež , Martin Rektoris , Tomáš Pevný , Václav Šmídl

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

Generative flow networks (GFlowNets) are amortized variational inference algorithms that are trained to sample from unnormalized target distributions over compositional objects. A key limitation of GFlowNets until this time has been that…

In this paper, we consider the problem of distributed inference in tree based networks. In the framework considered in this paper, distributed nodes make a 1-bit local decision regarding a phenomenon before sending it to the fusion center…

Information Theory · Computer Science 2016-11-17 Bhavya Kailkhura , Aditya Vempaty , Pramod K. Varshney

A number of recent papers have provided evidence that practical design questions about neural networks may be tackled theoretically by studying the behavior of random networks. However, until now the tools available for analyzing random…

Machine Learning · Statistics 2017-10-19 Samuel S. Schoenholz , Jeffrey Pennington , Jascha Sohl-Dickstein

In complex networks the degrees of adjacent nodes may often appear dependent -- which presents a modelling challenge. We present a working framework for studying networks with an arbitrary joint distribution for the degrees of adjacent…

Combinatorics · Mathematics 2020-08-25 Samuel , G. Balogh , Gergely Palla , Ivan Kryven

We prove asymptotic normality for the number of fringe subtrees isomorphic to any given tree in uniformly random trees with given vertex degrees. As applications, we also prove corresponding results for random labelled trees with given…

Probability · Mathematics 2023-12-08 Gabriel Berzunza Ojeda , Cecilia Holmgren , Svante Janson

Phylogenetic networks which are, as opposed to trees, suitable to describe processes like hybridization and horizontal gene transfer, play a substantial role in evolutionary research. However, while non-treelike events need to be taken into…

Populations and Evolution · Quantitative Biology 2022-07-06 Mareike Fischer , Tom Niklas Hamann , Kristina Wicke

We consider uniform random permutations drawn from a family enumerated through generating trees. We develop a new general technique to establish a central limit theorem for the number of consecutive occurrences of a fixed pattern in such…

Probability · Mathematics 2021-12-22 Jacopo Borga

We consider a family of random trees satisfying a Markov branching property. Roughly, this property says that the subtrees above some given height are independent with a law that depends only on their total size, the latter being either the…

Probability · Mathematics 2012-11-06 Bénédicte Haas , Grégory Miermont

One class of random walks with infinite memory, so called elephant random walks, are simple models describing anomalous diffusion. We present a surprising connection between these models and bond percolation on random recursive trees. We…

Statistical Mechanics · Physics 2016-03-23 Rüdiger Kürsten

In this paper we consider inhomogeneous Galton-Watson trees, and derive various moments for such processes: the number of vertices, the number of leaves, and the height of the tree. Also we make a simple condition of finiteness. We use…

Applications · Statistics 2025-05-09 Jakob G. Rasmussen , Troels Pedersen , Rasmus L. Olsen

In this paper a general class of tree algorithms is analyzed. It is shown that, by using an appropriate probabilistic representation of the quantities of interest, the asymptotic behavior of these algorithms can be obtained quite easily…

Probability · Mathematics 2016-08-16 Hanène Mohamed , Philippe Robert
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