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We consider a non-Markovian discrete-time random walk on $\mathbb{Z}$ with unbounded memory called the elephant random walk (ERW). We prove a strong invariance principle for the ERW. More specifically, we prove that, under a suitable…

Probability · Mathematics 2017-12-18 Cristian F. Coletti , Renato Gava , Gunter M. Schütz

The exponential family of random graphs represents an important and challenging class of network models. Despite their flexibility, conventionally used exponential random graphs have one shortcoming. They cannot directly model weighted…

Probability · Mathematics 2016-07-15 Mei Yin

A survey is presented of known results concerning simple random walk on the class of distance-regular graphs. One of the highlights is that electric resistance and hitting times between points can be explicitly calculated and given strong…

Probability · Mathematics 2013-01-29 Greg Markowsky

The rotor walk is a derandomized version of the random walk on a graph. On successive visits to any given vertex, the walker is routed to each of the neighboring vertices in some fixed cyclic order, rather than to a random sequence of…

Probability · Mathematics 2010-04-08 Alexander E. Holroyd , James Propp

The scaling properties of a random walker subject to the global constraint that it needs to visit each site an even number of times are determined. Such walks are realized in the equilibrium state of one dimensional surfaces that are…

Statistical Mechanics · Physics 2013-05-29 Jae Dong Noh , Hyunggyu Park , Doochul Kim , Marcel den Nijs

Random walk sampling methods have been widely used in graph sampling in recent years, while it has bias towards higher degree nodes in the sample. To overcome this deficiency, classical methods such as MHRW design weighted walking by…

Methodology · Statistics 2022-09-27 Xiao Qi

Node-level random walk has been widely used to improve Graph Neural Networks. However, there is limited attention to random walk on edge and, more generally, on $k$-simplices. This paper systematically analyzes how random walk on different…

Machine Learning · Computer Science 2023-10-31 Cai Zhou , Xiyuan Wang , Muhan Zhang

Dynamic graphs have emerged as an appropriate model to capture the changing nature of many modern networks, such as peer-to-peer overlays and mobile ad hoc networks. Most of the recent research on dynamic networks has only addressed the…

Data Structures and Algorithms · Computer Science 2011-02-02 Oksana Denysyuk , Luis Rodrigues

We consider excited random walk (ERW) on $\mathbb{Z}$ in environments with identical stacks of infinitely many cookies at each site, subject to the constraint that the total drift per site $\delta = \sum (2p_j - 1)$ is finite. Building on…

Probability · Mathematics 2021-03-10 Zachary Letterhos

In this work, we discuss the smoothly amnesia-reinforced multidimensional elephant random walk (MARW). The scaling limit of the MARW is shown to exist in the diffusive, critical and superdiffusive regimes. We also establish the almost sure…

Probability · Mathematics 2023-01-23 Jiaming Chen , Lucile Laulin

We prove an invariance principle for linearly edge reinforced random walks on $\gamma$-stable critical Galton-Watson trees, where $\gamma \in (1,2]$ and where the edge joining $x$ to its parent has rescaled initial weight $d(\rho,…

Probability · Mathematics 2025-09-30 George Andriopoulos , Eleanor Archer

We consider a particular Branching Random Walk in Random Environment (BRWRE) on $\sN_0$ started with one particle at the origin. Particles reproduce according to an offspring distribution (which depends on the location) and move either one…

Probability · Mathematics 2009-12-01 Christian Bartsch , Nina Gantert , Michael Kochler

We revisit an unpublished paper of Vervoort (2002) on the once reinforced random walk, and prove that this process is recurrent on any graph of the form $\mathbb{Z}\times \Gamma$, with $\Gamma$ a finite graph, for sufficiently large…

Probability · Mathematics 2018-07-20 Daniel Kious , Bruno Schapira , Arvind Singh

We study an intermittent random walk on a random network of scale-free degree distribution. The walk is a combination of simple random walks of duration $t_w$ and random long-range jumps. While the time the walker needs to cover all the…

Disordered Systems and Neural Networks · Physics 2015-06-25 A. Ramezanpour

Random walks (RWs) are fundamental stochastic processes with applications across physics, computer science, and information processing. A recent extension, the laser chaos decision-maker, employs chaotic time series from semiconductor…

Probability · Mathematics 2025-11-04 Akihiro Narimatsu , Tomoki Yamagami

Random walks are a fundamental tool for analyzing realistic complex networked systems and implementing randomized algorithms to solve diverse problems such as searching and sampling. For many real applications, their actual effect and…

Social and Information Networks · Computer Science 2018-03-09 Yuan Lin , Zhongzhi Zhang

Extreme events have low occurrence probabilities and display pronounced deviation from their average behaviour, such as earthquakes or power blackouts. Such extreme events occurring on the nodes of a complex network have been extensively…

Physics and Society · Physics 2022-02-09 Govind Gandhi , M. S. Santhanam

Applied to statistical physics models, the random cost algorithm enforces a Random Walk (RW) in energy (or possibly other thermodynamic quantities). The dynamics of this procedure is distinct from fixed weight updates. The probability for a…

Statistical Mechanics · Physics 2009-10-31 Bernd A. Berg , Ulrich H. E. Hansmann

Motivated by the article [M. Takei, Electron. J. Probab. 26 (2021), article no. 104], we study the limit behavior of linearly edge-reinforced random walks on the half-line $\mathbb{Z}_+$ with reinforcement parameter $\delta>0$, and each…

Probability · Mathematics 2026-01-23 Zechun Hu , Renming Song , Li Wang

Using edge weights is essential for modeling real-world systems where links possess relevant information, and preserving this information in low-dimensional representations is relevant for classification and prediction tasks. This paper…

Social and Information Networks · Computer Science 2025-08-12 Adilson Vital , Filipi N. Silva , Diego R. Amancio