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We investigate the hitting times of random walks on graphs, where a hitting time is defined as the number of steps required for a random walker to move from one node to another. While much of the existing literature focuses on calculating…

Probability · Mathematics 2025-11-10 Anuraag Kumar

Bootstrap percolation is a process that is used to model the spread of an infection on a given graph. In the model considered here each vertex is equipped with an individual threshold. As soon as the number of infected neighbors exceeds…

Probability · Mathematics 2022-10-25 Nils Detering , Thilo Meyer-Brandis , Konstantinos Panagiotou

We prove a metric space scaling limit for a critical random graph with independent and identically distributed degrees having power-law tail behaviour with exponent $\alpha+1$, where $\alpha \in (1,2)$. The limiting components are…

Probability · Mathematics 2021-08-02 Guillaume Conchon--Kerjan , Christina Goldschmidt

Testing for independence between graphs is a problem that arises naturally in social network analysis and neuroscience. In this paper, we address independence testing for inhomogeneous Erd\H{o}s-R\'{e}nyi random graphs on the same vertex…

Methodology · Statistics 2023-04-19 Yukun Song , Carey E. Priebe , Minh Tang

In causal inference on directed acyclic graphs, the orientation of edges is in general only recovered up to Markov equivalence classes. We study Markov equivalence classes of uniformly random directed acyclic graphs. Using a tower…

Probability · Mathematics 2024-10-01 Dominik Schmid , Allan Sly

We develop a Markov process viewpoint for discrete circular distributions motivated by directional-statistics settings where angles are observed on a finite grid and evolve over time. On the $m$-point discrete circle, the cycle graph, we…

Statistics Theory · Mathematics 2026-03-04 Sourav Majumdar

Locally Markov walks are natural generalizations of classical Markov chains, where instead of a particle moving independently of the past, it decides where to move next depending on the last action performed at the current location. We…

Probability · Mathematics 2025-12-02 Robin Kaiser , Lionel Levine , Ecaterina Sava-Huss

An Eulerian circuit in a directed graph is one of the most fundamental Graph Theory notions. Detecting if a graph $G$ has a unique Eulerian circuit can be done in polynomial time via the BEST theorem by de Bruijn, van Aardenne-Ehrenfest,…

Data Structures and Algorithms · Computer Science 2023-05-26 Nidia Obscura Acosta , Alexandru I. Tomescu

We consider the problem of determining the proportion of edges that are discovered in an Erdos-Renyi graph when one constructs all shortest paths from a given source node to all other nodes. This problem is equivalent to the one of…

Statistical Mechanics · Physics 2009-11-13 Vincent D. Blondel , Jean-Loup Guillaume , Julien M. Hendrickx , Raphael M. Jungers

Structure discovery in graphical models is the determination of the topology of a graph that encodes conditional independence properties of the joint distribution of all variables in the model. For some class of probability distributions,…

Machine Learning · Statistics 2016-04-07 Wacha Bounliphone , Matthew Blaschko

We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and…

Optimization and Control · Mathematics 2014-03-21 Jieqiang Wei , Arjan J. van der Schaft

A drawback of the classic approach for complexity analysis of distributed graph problems is that it mostly informs about the complexity of notorious classes of ``worst case'' graphs. Algorithms that are used to prove a tight (existential)…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-12 Philipp Schneider

We study the joint occurrence of large values of a Markov random field or undirected graphical model associated to a block graph. On such graphs, containing trees as special cases, we aim to generalize recent results for extremes of Markov…

Methodology · Statistics 2023-03-09 Stefka Asenova , Johan Segers

Since 1997 a considerable effort has been spent to study the mixing time of switch Markov chains on the realizations of graphic degree sequences of simple graphs. Several results were proved on rapidly mixing Markov chains on unconstrained,…

Let $w:[0,1]^2\rightarrow [0,1]$ be a symmetric function, and consider the random process $G(n,w)$, where vertices are chosen from $[0,1]$ uniformly at random, and $w$ governs the edge formation probability. Such a random graph is said to…

Combinatorics · Mathematics 2016-09-15 Huda Chuangpishit , Mahya Ghandehari , Jeannette Janssen

We are interested in the distribution of the number of faces across all the $2-$cell embeddings of a graph, which is equivalent to the distribution of genus by Euler's formula. In order to study this distribution, we consider the local…

Combinatorics · Mathematics 2024-06-12 Jesse Campion Loth

We define an analytic version of the graph property testing problem, which can be formulated as studying an unknown 2-variable symmetric function through sampling from its domain and studying the random graph obtained when using the…

Combinatorics · Mathematics 2008-03-11 Laszlo Lovasz , Balazs Szegedy

In this paper we study the problem of testing graph isomorphism (GI) in the CONGEST distributed model. In this setting we test whether the distributive network, $G_U$, is isomorphic to $G_K$ which is given as an input to all the nodes in…

Data Structures and Algorithms · Computer Science 2020-03-03 Reut Levi , Moti Medina

Graphical models are popular statistical tools which are used to represent dependent or causal complex systems. Statistically equivalent causal or directed graphical models are said to belong to a Markov equivalent class. It is of great…

Machine Learning · Statistics 2014-01-30 Yangbo He , Jinzhu Jia , Bin Yu

Distribution testing is a fundamental statistical task with many applications, but we are interested in a variety of problems where systematic mislabelings of the sample prevent us from applying the existing theory. To apply distribution…

Data Structures and Algorithms · Computer Science 2023-04-05 Renato Ferreira Pinto , Nathaniel Harms