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Related papers: Monotone graph limits and quasimonotone graphs

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A directed graph $D=(V(D),A(D))$ has a kernel if there exists an independent set $K\subseteq V(D)$ such that every vertex $v\in V(D)-K$ has an ingoing arc $u\mathbin{\longrightarrow}v$ for some $u\in K$. There are directed graphs that do…

Combinatorics · Mathematics 2021-10-05 Allan van Hulst

We study the chromatic symmetric function on graphs, and show that its kernel is spanned by the modular relations. We generalize this result to the chromatic quasisymmetric function on hypergraphic polytopes, a family of generalized…

Combinatorics · Mathematics 2020-03-31 Raul Penaguiao

We present a new notion of limits of weighted directed graphs of growing size based on convergence of their random quotients. These limits are specified in terms of random exchangeable measures on the unit square. We call our limits…

Combinatorics · Mathematics 2026-03-24 Eitan Levin , Venkat Chandrasekaran

Words are sequences of letters over a finite alphabet. We study two intimately related topics for this object: quasi-randomness and limit theory. With respect to the first topic we investigate the notion of uniform distribution of letters…

Combinatorics · Mathematics 2021-09-01 Hiêp Hàn , Marcos Kiwi , Matías Pavez-Signé

We investigate when limits of graphs (graphons) and permutations (permutons) are uniquely determined by finitely many densities of their substructures, i.e., when they are finitely forcible. Every permuton can be associated with a graphon…

Combinatorics · Mathematics 2016-02-23 Roman Glebov , Andrzej Grzesik , Tereza Klimosova , Daniel Kral

Graph neural networks (GNNs) are the de facto standard deep learning architectures for machine learning on graphs. This has led to a large body of work analyzing the capabilities and limitations of these models, particularly pertaining to…

Machine Learning · Computer Science 2024-11-11 Sam Adam-Day , Theodor Mihai Iliant , İsmail İlkan Ceylan

We study the relation between the growth rate of a graph property and the entropy of the graph limits that arise from graphs with that property. In particular, for hereditary classes we obtain a new description of the colouring number,…

Combinatorics · Mathematics 2013-12-20 Hamed Hatami , Svante Janson , Balázs Szegedy

We study limits of convergent sequences of string graphs, that is, graphs with an intersection representation consisting of curves in the plane. We use these results to study the limiting behavior of a sequence of random string graphs. We…

Combinatorics · Mathematics 2014-03-13 Svante Janson , Andrew J. Uzzell

A total dominating set of a graph $G=(V,E)$ is a subset $D \subseteq V$ such that every vertex in $V$ is adjacent to some vertex in $D$. Finding a total dominating set of minimum size is NP-hard on planar graphs and W[2]-complete on general…

Data Structures and Algorithms · Computer Science 2023-06-22 Valentin Garnero , Ignasi Sau

We answer a question of Benjamini and Schramm by proving that under reasonable conditions, quotienting a graph strictly increases the value of its percolation critical parameter $p_c$. More precisely, let $\mathcal{G}=(V,E)$ be a…

Probability · Mathematics 2018-09-17 Sébastien Martineau , Franco Severo

A graph property is monotone if it is closed under removal of vertices and edges. In this paper we consider the following edge-deletion problem; given a monotone property P and a graph G, compute the smallest number of edge deletions that…

Combinatorics · Mathematics 2007-07-03 Noga Alon , Asaf Shapira , Benny Sudakov

We prove measurable analogues of Whitney's classical theorems on weak isomorphisms of finite graphs. In the setting of locally finite graphings, we introduce a notion of weak isomorphism as an edge-measure-preserving Borel bijection that…

Combinatorics · Mathematics 2026-05-18 Márton Borbényi , Grigory Terlov , László Márton Tóth

Graph convolutional networks (GCNs) are a widely used method for graph representation learning. To elucidate the capabilities and limitations of GCNs, we investigate their power, as a function of their number of layers, to distinguish…

Machine Learning · Statistics 2020-05-14 Abram Magner , Mayank Baranwal , Alfred O. Hero

For a symmetric bounded measurable function W on [0,1]^2, "moments" of W can be defined as values t(F,W) indexed by simple graphs. We prove that every such function is determined by its moments up to a measure preserving transformation of…

Combinatorics · Mathematics 2008-12-08 Christian Borgs , Jennifer Chayes , Laszlo Lovasz

We investigate quantum graphs with infinitely many vertices and edges without the common restriction on the geometry of the underlying metric graph that there is a positive lower bound on the lengths of its edges. Our central result is a…

Mathematical Physics · Physics 2018-10-30 Pavel Exner , Aleksey Kostenko , Mark Malamud , Hagen Neidhardt

Graph kernels are often used in bioinformatics and network applications to measure the similarity between graphs; therefore, they may be used to construct efficient graph classifiers. Many graph kernels have been developed thus far, but to…

Quantum Physics · Physics 2022-11-01 Kaito Kishi , Takahiko Satoh , Rudy Raymond , Naoki Yamamoto , Yasubumi Sakakibara

Whitney's Theorem states that every graph, different from $K_3$ or $K_{1,3}$, is uniquely determined by its line graph. A $1$-line graph of a multi-graph is the graph with as vertices the edges of the multi-graph, and two edges adjacent if…

Combinatorics · Mathematics 2021-05-19 Hans Cuypers

A kernel of a directed graph is a subset of vertices that is both independent and absorbing (every vertex not in the kernel has an out-neighbour in the kernel). Not all directed graphs contain kernels, and computing a kernel or deciding…

Discrete Mathematics · Computer Science 2024-05-20 Bruno Jartoux

Graphons are limit objects of sequences of graphs and are used to analyze the behavior of large graphs. Recently, graphon signal processing has been developed to study signal processing on large graphs. A major limitation of this approach…

Signal Processing · Electrical Eng. & Systems 2024-03-26 Feng Ji , Xingchao Jian , Wee Peng Tay

We consider the problem of classifying graphs using graph kernels. We define a new graph kernel, called the generalized shortest path kernel, based on the number and length of shortest paths between nodes. For our example classification…

Data Structures and Algorithms · Computer Science 2015-11-20 Linus Hermansson , Fredrik D. Johansson , Osamu Watanabe
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