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Related papers: Asymptotic study of subcritical graph classes

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We prove local convergence results for the uniformly random, labelled or unlabelled, graphs from subcritical families. As an example special case, we prove Benjamini-Schramm convergence for the uniform random unlabelled tree. We introduce a…

Combinatorics · Mathematics 2016-11-28 Agelos Georgakopoulos , Stephan Wagner

Let $H$ be a fixed graph and $\mathcal{G}$ a subcritical graph class. In this paper we show that the number of occurrences of $H$ (as a subgraph) in a uniformly at random graph of size $n$ in $\mathcal{G}$ follows a normal limiting…

Combinatorics · Mathematics 2018-08-06 Michael Drmota , Lander Ramos , Juanjo Rué

A graph $G$ is called universal for a family of graphs $\mathcal{F}$ if it contains every element $F \in \mathcal{F}$ as a subgraph. Let $\mathcal{F}(n,2)$ be the family of all graphs with maximum degree $2$. Ferber, Kronenberg, and Luh…

Combinatorics · Mathematics 2019-02-19 Olaf Parczyk

Random planar graphs have been the subject of much recent work. Many basic properties of the standard uniform random planar graph P_{n}, by which we mean a graph chosen uniformly at random from the set of all planar graphs with vertex set…

Combinatorics · Mathematics 2013-07-23 Chris Dowden

We deal with a general preferential attachment graph model with multiple type edges. The types are chosen randomly, in a way that depends on the evolution of the graph. In the $N$-type case, we define the (generalized) degree of a given…

Probability · Mathematics 2019-03-25 Ágnes Backhausz , Bence Rozner

Computing the embedding distribution of a given graph is a fundamental question in topological graph theory. In this article, we extend our viewpoint to a sequence of graphs and consider their asymptotic embedding distributions, which are…

Combinatorics · Mathematics 2025-07-22 Yichao Chen , Wenjie Fang , Zhicheng Gao , Jinlian Zhang

There has been much recent interest in random graphs sampled uniformly from the n-vertex graphs in a suitable minor-closed class, such as the class of all planar graphs. Here we use combinatorial and probabilistic methods to investigate a…

Combinatorics · Mathematics 2012-10-10 Colin McDiarmid

We propose to study the problem of few shot graph classification in graph neural networks (GNNs) to recognize unseen classes, given limited labeled graph examples. Despite several interesting GNN variants being proposed recently for node…

Machine Learning · Computer Science 2022-05-03 Jatin Chauhan , Deepak Nathani , Manohar Kaul

Let $K_n$ be the complete graph with $n$ vertices and $c_1, c_2, ..., c_r$ be $r$ different colors. Suppose we randomly and uniformly color the edges of $K_n$ in $c_1, c_2, ..., c_r$. Then we get a random graph, denoted by…

Combinatorics · Mathematics 2007-11-27 Xueliang Li , Jie Zheng

A hypergraph is simple if it has no loops and no repeated edges, and a hypergraph is linear if it is simple and each pair of edges intersects in at most one vertex. For $n\geq 3$, let $r= r(n)\geq 3$ be an integer and let $\boldsymbol{k} =…

Combinatorics · Mathematics 2016-07-20 Vladimir Blinovsky , Catherine Greenhill

We find an asymptotic enumeration formula for the number of simple $r$-uniform hypergraphs with a given degree sequence, when the number of edges is sufficiently large. The formula is given in terms of the solution of a system of equations.…

Combinatorics · Mathematics 2022-05-18 Catherine Greenhill , Mikhail Isaev , Tamás Makai , Brendan D. McKay

Unsupervised graph representation learning aims to learn low-dimensional node embeddings without supervision while preserving graph topological structures and node attributive features. Previous graph neural networks (GNN) require a large…

Machine Learning · Computer Science 2020-09-04 Yanqiao Zhu , Yichen Xu , Feng Yu , Shu Wu , Liang Wang

We investigate topological, combinatorial, statistical, and enumeration properties of finite graphs with high Kolmogorov complexity (almost all graphs) using the novel incompressibility method. Example results are: (i) the mean and variance…

Combinatorics · Mathematics 2007-05-23 Harry Buhrman , Ming Li , John Tromp , Paul Vitanyi

As proved by Kahn, the chromatic number and fractional chromatic number of a line graph agree asymptotically. That is, for any line graph $G$ we have $\chi(G) \leq (1+o(1))\chi_f(G)$. We extend this result to quasi-line graphs, an important…

Discrete Mathematics · Computer Science 2011-02-07 Andrew D. King , Bruce Reed

Node classification on graphs is a significant task with a wide range of applications, including social analysis and anomaly detection. Even though graph neural networks (GNNs) have produced promising results on this task, current…

Machine Learning · Computer Science 2023-06-16 Jingyang Yuan , Xiao Luo , Yifang Qin , Yusheng Zhao , Wei Ju , Ming Zhang

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

The main goal of this paper is to determine the asymptotic behavior of the number $X_n$ of cut-vertices in random planar maps with $n$ edges. It is shown that $X_n/n \to c$ in probability (for some explicit $c>0$). For so-called subcritical…

Probability · Mathematics 2021-04-30 Michael Drmota , Marc Noy , Benedikt Stufler

The graph isomorphism problem is a main problem which has numerous applications in different fields. Thus, finding an efficient and easy to implement method to discriminate non-isomorphic graphs is valuable. In this paper, a new method is…

Combinatorics · Mathematics 2016-11-08 Ameneh Farhadian

We enumerate rooted 2-connected and 3-connected surface maps with respect to vertices and edges. We also derive the bivariate version of the large face-width result for random 3-connected maps. These results are then used to derive…

Combinatorics · Mathematics 2010-03-16 E. A. Bender , Z. Gao

Nowadays, graph-structured data are increasingly used to model complex systems. Meanwhile, detecting anomalies from graph has become a vital research problem of pressing societal concerns. Anomaly detection is an unsupervised learning task…

Machine Learning · Computer Science 2021-03-29 Xuhong Wang , Baihong Jin , Ying Du , Ping Cui , Yupu Yang