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We define a random walk problem which admits analytic results, on a class of infinite periodic lattices which are directed and colored. Our approach is motivated from the fact that such lattices arise in string theoretic constructs of…

Statistical Mechanics · Physics 2012-01-10 Subhash Mahapatra , Prabwal Phukon , Tapobrata Sarkar

The node2vec random walk is a non-Markovian random walk on the vertex set of a graph, widely used for network embedding and exploration. This random walk model is defined in terms of three parameters which control the probability of,…

Probability · Mathematics 2026-04-16 Luca Avena , Gianmarco Bet , Lars Schroeder , Clara Stegehuis

This paper studies the on- and off-diagonal upper estimate and the two-sided transition probability estimate of random walks on weighted graphs.

Probability · Mathematics 2008-01-16 Andras Telcs

Consider the random Cayley graph of a finite group $G$ with respect to $k$ generators chosen uniformly at random, with $1 \ll k \lesssim \log |G|$. The results of this article supplement those in the three main papers on random Cayley…

Probability · Mathematics 2021-02-05 Jonathan Hermon , Sam Olesker-Taylor

Random walk algorithms are crucial for sampling and approximation problems in statistical physics and theoretical computer science. The mixing property is necessary for Markov chains to approach stationary distributions and is facilitated…

Quantum Physics · Physics 2024-12-02 Shyam Dhamapurkar , Yuhang Dang , Saniya Wagh , Xiu-Hao Deng

Random walks on general graphs play an important role in the understanding of the general theory of stochastic processes. Beyond their fundamental interest in probability theory, they arise also as simple models of physical systems. A brief…

Probability · Mathematics 2016-09-07 Massimo Campanino , Dimitri Petritis

We present the first linear time complexity randomized algorithms for unbiased approximation of the celebrated family of general random walk kernels (RWKs) for sparse graphs. This includes both labelled and unlabelled instances. The…

Machine Learning · Computer Science 2024-10-16 Krzysztof Choromanski , Isaac Reid , Arijit Sehanobish , Avinava Dubey

We show that for a sequence of random graphs Brouwer's conjecture holds true with probability tending to one as the number of vertices tends to infinity. Surprisingly, it was found that a similar statement holds true for weighted graphs…

Combinatorics · Mathematics 2019-06-14 Israel Rocha

Random walks are widely used for mining networks due to the computational efficiency of computing them. For instance, graph representation learning learns a d-dimensional embedding space, so that the nodes that tend to co-occur on random…

Social and Information Networks · Computer Science 2024-05-24 Sam F. L. Windels , Noel Malod-Dognin , Natasa Przulj

We present an analytical approach to study simple symmetric random walks (RWs) on a crossing geometry consisting of a plane square lattice crossed by $n_l$ number of lines that all meet each other at a single point (the origin) on the…

Statistical Mechanics · Physics 2019-09-02 Reza Sepehrinia , Abbas Ali Saberi , Hor Dashti-Naserabadi

We present a novel mechanism to improve the accuracy of the recently-introduced class of graph random features (GRFs). Our method induces negative correlations between the lengths of the algorithm's random walks by imposing antithetic…

Machine Learning · Statistics 2023-05-23 Isaac Reid , Krzysztof Choromanski , Adrian Weller

We define the Uniform Random Walk (URW) on a connected, locally finite graph as the weak limit of the uniform walk of length $n$ starting at a fixed vertex. When the limit exists, it is necessarily Markovian and is independent of the…

Probability · Mathematics 2025-12-11 Miklos Abert , Adam Arras , Jaelin Kim

We give a deterministic, nearly logarithmic-space algorithm that given an undirected graph $G$, a positive integer $r$, and a set $S$ of vertices, approximates the conductance of $S$ in the $r$-step random walk on $G$ to within a factor of…

Computational Complexity · Computer Science 2019-11-26 Jack Murtagh , Omer Reingold , Aaron Sidford , Salil Vadhan

We give a short proof of Theorem 2.1 from [MR07], stating that the linearly edge reinforced random walk (ERRW) on a locally finite graph is recurrent if and only if it returns to its starting point almost surely. This result was proved in…

Probability · Mathematics 2009-11-30 Laurent Tournier

We investigate invariants for random elements of different hyperbolic groups. We provide a method, using Cayley graphs of groups, to compute the probability distribution of the minimal length of a random word, and explicitly compute the…

Mathematical Physics · Physics 2007-05-23 Sergei Nechaev , Raphael Voituriez

This article introduces a model for interacting vertex-reinforced random walks, each taking values on a complete sub-graph of a locally finite undirected graph. The transition probability for a walk to a given vertex depends on the…

Probability · Mathematics 2025-08-25 Fernando P. A. Prado , Rafael A. Rosales

These notes cover one of the topics programmed for the St Petersburg School in Probability and Statistical Physics of June 2012. The aim is to review recent mathematical developments in the field of random walks in random environment. Our…

Probability · Mathematics 2014-06-20 Gerard Ben Arous , Alexander Fribergh

We study Vertex-Reinforced-Random-Walk on the complete graph with weights of the form $w(n)=n^\alpha$, with $\alpha>1$. Unlike for the Edge-Reinforced-Random-Walk, which in this case localizes a.s. on 2 sites, here we observe various phase…

Probability · Mathematics 2013-10-08 Michel Benaïm , Olivier Raimond , Bruno Schapira

Consider a simple graph in which a random walk begins at a given vertex. It moves at each step with equal probability to any neighbor of its current vertex, and ends when it has visited every vertex. We call such a random walk a random…

Combinatorics · Mathematics 2023-03-14 Calum Buchanan , Paul Horn , Puck Rombach

Graph-structured data arise in wide applications, such as computer vision, bioinformatics, and social networks. Quantifying similarities among graphs is a fundamental problem. In this paper, we develop a framework for computing graph…

Machine Learning · Statistics 2018-09-11 Zhen Zhang , Mianzhi Wang , Yijian Xiang , Yan Huang , Arye Nehorai
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