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Fokker-Planck equations represent a suitable description of the finite-time behavior for a large class of particle systems as the size of the population tends to infinity. Recently, the theory of graph limits has been introduced in the…

Probability · Mathematics 2022-03-24 Fabio Coppini

Current methods of graph signal processing rely heavily on the specific structure of the underlying network: the shift operator and the graph Fourier transform are both derived directly from a specific graph. In many cases, the network is…

Signal Processing · Electrical Eng. & Systems 2023-03-31 Kathryn Beck , Mahya Ghandehari , Jeannette Janssen , Nauzer Kalyaniwalla

A graph operator is a function $\Gamma$ defined on some set of graphs such that whenever two graphs $G$ and $H$ are isomorphic, written $G\simeq H$, then $\Gamma(G)\simeq \Gamma(H)$. For a graph $G$ not in the domain of $\Gamma$, we put…

Combinatorics · Mathematics 2024-12-17 Severino V. Gervacio

Motivated by the theory of graph limits, we introduce and study the convergence and limits of linear representations of finite groups over finite fields. The limit objects are infinite dimensional representations of free groups in…

Rings and Algebras · Mathematics 2015-11-20 Gabor Elek

We provide a doubly exponential upper bound in $p$ on the size of forbidden pivot-minors for symmetric or skew-symmetric matrices over a fixed finite field $\mathbb{F}$ of linear rank-width at most $p$. As a corollary, we obtain a doubly…

Combinatorics · Mathematics 2014-12-24 Mamadou Moustapha Kanté , O-joung Kwon

Random matrix theory has played an important role in recent work on statistical network analysis. In this paper, we review recent results on regimes of concentration of random graphs around their expectation, showing that dense graphs…

Statistics Theory · Mathematics 2018-01-29 Can M. Le , Elizaveta Levina , Roman Vershynin

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

We prove $L^p$ boundedness results, $p > 2$, for local maximal averaging operators over a smooth 2D hypersurface $S$ with either a $C^1$ density function or a density function with a singularity that grows as $|(x,y)|^{-\beta}$ for $\beta <…

Classical Analysis and ODEs · Mathematics 2018-10-24 Michael Greenblatt

This paper proves limit theorems for the number of monochromatic edges in uniform random colorings of general random graphs. These can be seen as generalizations of the birthday problem (what is the chance that there are two friends with…

Probability · Mathematics 2018-02-13 Bhaswar B. Bhattacharya , Persi Diaconis , Sumit Mukherjee

We study the boundedness problem for maximal operators $\mathcal{M}$ associated to averages along families of hypersurfaces $S$ of finite type in $\mathbb{R}^n.$ In this paper, we prove that if $S$ is a finite type hypersurface which is of…

Classical Analysis and ODEs · Mathematics 2016-09-28 Ramesh Manna

Guided by the theory of graph limits, we investigate a variant of the cut metric for limit objects of sequences of discrete probability distributions. Apart from establishing basic results, we introduce a natural operation called {\em…

Combinatorics · Mathematics 2020-12-02 Amin Coja-Oghlan , Max Hahn-Klimroth

We consider large uniform labeled random graphs in different classes with few induced $P_4$ ($P_4$ is the graph consisting of a single line of $4$ vertices) which generalize the case of cographs. Our main result is the convergence to a…

Probability · Mathematics 2023-10-25 Théo Lenoir

This paper concerns discrete-time occupancy processes on a finite graph. Our results can be formulated in two theorems, which are stated for vertex processes, but also applied to edge process (e.g., dynamic random graphs). The first theorem…

Probability · Mathematics 2024-10-10 Davide Sclosa , Michel Mandjes , Christian Bick

Formal Laplace operators are analyzed for a large class of resistance networks with vertex weights. The graphs are completed with respect to the minimal resistance path metric. Compactness and a novel connectivity hypothesis for the…

Functional Analysis · Mathematics 2011-09-15 Robert Carlson

We discuss how graph expansion is related to the behavior of $L^{p}$-functions on the covering tree. We show that the non-trivial eigenvalues of the adjacency operator on aa $(q+1)$-regular graph are bounded by $q^{1/p}+q^{(p-1)/p}$ - the…

Combinatorics · Mathematics 2022-02-25 Amitay Kamber

The collective dynamics of interacting dynamical units on a network crucially depends on the properties of the network structure. Rather than considering large but finite graphs to capture the network, one often resorts to graph limits and…

Dynamical Systems · Mathematics 2024-08-06 Christian Bick , Davide Sclosa

We prove $L^p$ bounds in the range $1<p<\infty$ for a maximal dyadic sum operator on $\rn$. This maximal operator provides a discrete multidimensional model of Carleson's operator. Its boundedness is obtained by a simple twist of the proof…

Classical Analysis and ODEs · Mathematics 2007-05-23 Loukas Grafakos , Terence Tao , Erin Terwilleger

We study the design of graph filters to implement arbitrary linear transformations between graph signals. Graph filters can be represented by matrix polynomials of the graph-shift operator, which captures the structure of the graph and is…

Information Theory · Computer Science 2017-05-23 Santiago Segarra , Antonio G. Marques , Alejandro Ribeiro

For a constant $\gamma \in[0,1]$ and a graph $G$, let $\omega_{\gamma}(G)$ be the largest integer $k$ for which there exists a $k$-vertex subgraph of $G$ with at least $\gamma\binom{k}{2}$ edges. We show that if $0<p<\gamma<1$ then…

Combinatorics · Mathematics 2018-03-29 Paul Balister , Béla Bollobás , Julian Sahasrabudhe , Alexander Veremyev

Despite the celebrated popularity of Graph Neural Networks (GNNs) across numerous applications, the ability of GNNs to generalize remains less explored. In this work, we propose to study the generalization of GNNs through a novel…

Machine Learning · Computer Science 2024-04-17 Shouheng Li , Dongwoo Kim , Qing Wang