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Given a set of graphs from some unknown family, we want to generate new graphs from that family. Recent methods use diffusion on either graph embeddings or the discrete space of nodes and edges. However, simple changes to embeddings (say,…

Machine Learning · Computer Science 2026-05-08 Rahul Nandakumar , Deepayan Chakrabarti

We propose a model of random walks on weighted graphs where the weights are interval valued, and connect it to reversible imprecise Markov chains. While the theory of imprecise Markov chains is now well established, this is a first attempt…

Optimization and Control · Mathematics 2016-09-20 Damjan Škulj

We consider a branching random walk (BRW) taking its values in the $\mathtt{b}$-ary rooted tree $\mathbb W_{ \mathtt{b}}$ (i.e. the set of finite words written in the alphabet $\{ 1, \ldots, \mathtt{b} \}$, with $\mathtt{b}\! \geq \! 2$).…

Probability · Mathematics 2022-01-24 Thomas Duquesne , Robin Khanfir , Shen Lin , Niccolo Torri

The infinite two-sided loop-erased random walk (LERW) is a measure on infinite self-avoiding walks that can be viewed as giving the law of the `middle part' of an infinite LERW loop going through 0 and infinity. In this note we derive…

Probability · Mathematics 2019-11-20 Christian Beneš , Gregory F. Lawler , Fredrik Viklund

This paper proposes an attributed network growth model. Despite the knowledge that individuals use limited resources to form connections to similar others, we lack an understanding of how local and resource-constrained mechanisms explain…

Social and Information Networks · Computer Science 2019-04-17 Harshay Shah , Suhansanu Kumar , Hari Sundaram

Hypergraph has been selected as a powerful candidate for characterizing higher-order networks and has received increasing attention in recent years. In this article, we study random walks with resetting on hypergraph by utilizing spectral…

Social and Information Networks · Computer Science 2025-05-08 Fei Ma , Xincheng Hu , Haobin Shi , Wei Pan , Ping Wang

We study a general class of random walks driven by a uniquely ergodic Markovian environment. Under a coupling condition on the environment we obtain strong ergodicity properties for the environment as seen from the position of the walker,…

Probability · Mathematics 2013-10-04 Frank Redig , Florian Völlering

Motivated by novel results in the theory of complex adaptive systems, we analyze the dynamics of random walks in which the jumping probabilities are {\it time-dependent}. We determine the survival probability in the presence of an absorbing…

Condensed Matter · Physics 2016-08-31 Shahar Hod

We present results relating mixing times to the intersection time of branching random walk (BRW) in which the logarithm of the expected number of particles grows at rate of the spectral-gap $\mathrm{gap}$ . This is a finite state space…

Probability · Mathematics 2022-03-03 Jonathan Hermon

We introduce a formalism based on a continuous time approximation, to study the characteristics of Page Rank random walks. We find that the diffusion of the occupancy probability has a dynamics that exponentially "forgets" the initial…

Statistical Mechanics · Physics 2020-07-17 Emilio Aced Fuentes , Simone Santini

We consider a recurrent random walk (RW) in random environment (RE) on a strip. We prove that if the RE is i. i. d. and its distribution is not supported by an algebraic subsurface in the space of parameters defining the RE then the RW…

Probability · Mathematics 2009-11-13 Erwin Bolthausen , Ilya Goldsheid

We consider a one-dimensional simple random walk killed by quenched soft obstacles. The position of the obstacles is drawn according to a renewal process with a power-law increment distribution. In a previous work, we computed the…

Probability · Mathematics 2024-04-17 Julien Poisat , Francois Simenhaus

In this paper, we study the fundamental problem of random walk for network embedding. We propose to use non-Markovian random walk, variants of vertex-reinforced random walk (VRRW), to fully use the history of a random walk path. To solve…

Social and Information Networks · Computer Science 2020-02-12 Wenyi Xiao , Huan Zhao , Vincent W. Zheng , Yangqiu Song

In this work, we propose a scheme that provides an analytical estimate for the time-dependent degree distribution of some networks. This scheme maps the problem into a random walk in degree space, and then we choose the paths that are…

Physics and Society · Physics 2017-01-25 H. L. Casa Grande , M. Cotacallapa , M. O. Hase

We present the first rigorous quantitative analysis of once-reinforced random walks (ORRW) on general graphs, based on a novel change of measure formula.~This enables us to prove large deviations estimates for the range of the walk to have…

Probability · Mathematics 2025-09-05 Andrea Collevecchio , Pierre Tarrès

Subordinating a random walk to a renewal process yields a continuous time random walk (CTRW) model for diffusion, including the possibility of anomalous diffusion. Transition densities of scaling limits of power law CTRWs have been shown to…

Probability · Mathematics 2010-05-14 Peter Straka , Bruce Ian Henry

We study the properties of random walks on complex trees. We observe that the absence of loops reflects in physical observables showing large differences with respect to their looped counterparts. First, both the vertex discovery rate and…

Statistical Mechanics · Physics 2008-10-21 Andrea Baronchelli , Michele Catanzaro , Romualdo Pastor-Satorras

We consider a family of one-dimensional self interacting walks whose dynamics characterized by a monotone weight function $w$ on $\mathbb{N}\cup \{0\}$. The weight function takes the form $w(n) = (1 + 2^p Bn^{-p} + O(n^{-1-\kappa}))^{-1}$,…

Probability · Mathematics 2025-04-01 Xiaoyu Liu , Zhe Wang

It is known that maximal entropy random walks and partition functions that count long paths on graphs tend to become localized near nodes with a high degree. Here, we revisit the simplest toy model of such a localization: a regular tree of…

Statistical Mechanics · Physics 2023-09-22 Alexey V. Gulyaev , Mikhail V. Tamm

In recent years, non-parametric methods utilizing random walks on graphs have been used to solve a wide range of machine learning problems, but in their simplest form they do not scale well due to the quadratic complexity. In this paper, a…

Machine Learning · Computer Science 2012-10-19 Saeed Amizadeh , Bo Thiesson , Milos Hauskrecht