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Our understanding of the dynamics of complex networked systems has increased significantly in the last two decades. However, most of our knowledge is built upon assuming pairwise relations among the system's components. This is often an…

Physics and Society · Physics 2020-04-15 Guilherme Ferraz de Arruda , Giovanni Petri , Yamir Moreno

Let $G=(V, E)$ be a locally finite connected graph satisfying curvature-dimension conditions ($CDE(n, 0)$ or its strengthened version $CDE'(n, 0))$) and polynomial volume growth conditions of degree $m$. We systematically establish sharp…

Analysis of PDEs · Mathematics 2025-05-13 Yuanyang Hu

Motivated by applications in data science, we study partial differential equations on graphs. By a classical fixed-point argument, we show existence and uniqueness of solutions to a class of nonlocal continuity equations on graphs. We…

Analysis of PDEs · Mathematics 2023-06-06 A. Esposito , F. S. Patacchini , A. Schlichting

We derive exact equations that determine the spectra of undirected and directed sparsely connected regular graphs containing loops of arbitrary length. The implications of our results to the structural and dynamical properties of networks…

Statistical Mechanics · Physics 2011-12-07 F. L. Metz , I. Neri , D. Bollé

We establish a central limit theorem for the sum of $\epsilon$-independent random variables, extending both the classical and free probability setting. Central to our approach is the use of graphon limits to characterize the limiting…

Probability · Mathematics 2024-12-02 Guillaume Cébron , Patrick Oliveira Santos , Pierre Youssef

Computing the size of maximum independent sets is a NP-hard problem for fixed graphs. Characterizing and designing efficient algorithms to estimate this independence number for random graphs are notoriously difficult and still largely open…

Probability · Mathematics 2020-10-01 Paola Bermolen , Matthieu Jonckheere , Federico Larroca , Manuel Saenz

In this work we provide a new technique to design fast approximation algorithms for graph problems where the points of the graph lie in a metric space. Specifically, we present a sampling approach for such metric graphs that, using a…

Data Structures and Algorithms · Computer Science 2018-07-26 Hossein Esfandiari , Michael Mitzenmacher

This work discusses the homogenization analysis for diffusion processes on scale-free metric graphs, using weak variational formulations. The oscillations of the diffusion coefficient along the edges of a metric graph induce internal…

Analysis of PDEs · Mathematics 2016-05-31 Fernando A. Morales , Daniel E. Restrepo

We study diffusion-type equations supported on structures that are randomly varying in time. After settling the issue of well-posedness, we focus on the asymptotic behavior of solutions: our main result gives sufficient conditions for…

Dynamical Systems · Mathematics 2020-04-28 Stefano Bonaccorsi , Francesca Cottini , Delio Mugnolo

The paper is devoted to the problem of establishing right-convergence of sparse random graphs. This concerns the convergence of the logarithm of number of homomorphisms from graphs or hyper-graphs $\G_N, N\ge 1$ to some target graph $W$.…

Probability · Mathematics 2012-02-15 David Gamarnik

In this work, we introduce novel algorithms for label propagation and self-training using fractional heat kernel dynamics with a source term. We motivate the methodology through the classical correspondence of information theory with the…

Machine Learning · Computer Science 2025-10-07 Farid Bozorgnia , Vyacheslav Kungurtsev , Shirali Kadyrov , Mohsen Yousefnezhad

Gas transport and other complex real-world challenges often require solving and controlling partial differential equations (PDEs) defined on graph structures, which typically demand substantial memory and computational resources. The Random…

Numerical Analysis · Mathematics 2025-06-16 Martín Hernández , Enrique Zuazua

This article gives an overview of the emerging literature on large deviations for random graphs. Written for the general mathematical audience, the article begins with a short introduction to the theory of large deviations. This is followed…

Probability · Mathematics 2016-04-29 Sourav Chatterjee

Theoretical analyses for graph learning methods often assume a complete observation of the input graph. Such an assumption might not be useful for handling any-size graphs due to the scalability issues in practice. In this work, we develop…

Machine Learning · Computer Science 2021-11-08 Takanori Maehara , Hoang NT

The theory of graphons is an important tool in understanding properties of large networks. We investigate a power-law random graph model and cast it in the graphon framework. The distinctively different structures of the limit graph are…

Probability · Mathematics 2022-08-22 Mei Yin

We propose numerical schemes for the approximate solution of problems defined on the edges of a one-dimensional graph. In particular, we consider linear transport and a drift-diffusion equations, and discretize them by extending Finite…

Numerical Analysis · Mathematics 2024-11-01 Beatrice Crippa , Anna Scotti , Andrea Villa

Recently, variants of many classical extremal theorems have been proved in the random environment. We, complementing existing results, extend the Erd\H{o}s-Gallai Theorem in random graphs. In particular, we determine, up to a constant…

Combinatorics · Mathematics 2020-01-15 József Balogh , Andrzej Dudek , Lina Li

This paper investigates properties of the class of graphs based on exchangeable point processes. We provide asymptotic expressions for the number of edges, number of nodes and degree distributions, identifying four regimes: (i) a dense…

Statistics Theory · Mathematics 2025-02-06 François Caron , Francesca Panero , Judith Rousseau

We examine the heterogeneous responses of individual nodes in sparse networks to the random removal of a fraction of edges. Using the message-passing formulation of percolation, we discover considerable variation across the network in the…

Statistical Mechanics · Physics 2017-09-13 Reimer Kuehn , Tim Rogers

We give a simple argument to obtain $\mathrm{L}^p$-boundedness for heat semigroups associated to uniformly strongly elliptic systems on $\mathbb{R}^d$ by using Stein interpolation between Gaussian estimates and hypercontractivity. Our…

Analysis of PDEs · Mathematics 2023-11-21 Tim Böhnlein , Moritz Egert
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