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We investigate the threshold probability for connectivity of sparse graphs under weak assumptions. As a corollary this completely solve the problem for Cartesian powers of arbitrary graphs. In detail, let $G$ be a connected graph on $k$…

Combinatorics · Mathematics 2013-12-04 Felix Joos

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

Analyzing the mixing time of random walks is a well-studied problem with applications in random sampling and more recently in graph partitioning. In this work, we present new analysis of random walks and evolving sets using more…

Data Structures and Algorithms · Computer Science 2015-07-09 Siu On Chan , Tsz Chiu Kwok , Lap Chi Lau

We study the number of isolated nodes in a soft random geometric graph whose vertices constitute a Poisson process on the torus of length L (the line segment [0,L] with periodic boundary conditions), and where an edge is present between two…

Probability · Mathematics 2022-10-21 Michael Wilsher , Carl Dettmann , Ayalvadi Ganesh

In recent years, graph neural networks (GNNs) have gained increasing popularity and have shown very promising results for data that are represented by graphs. The majority of GNN architectures are designed based on developing new…

Machine Learning · Statistics 2021-10-05 Anahita Iravanizad , Edgar Ivan Sanchez Medina , Martin Stoll

Motivated by the increasing need to understand the algorithmic foundations of distributed large-scale graph computations, we study a number of fundamental graph problems in a message-passing model for distributed computing where $k \geq 2$…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-07-07 Gopal Pandurangan , Peter Robinson , Michele Scquizzato

Graph neural networks (GNNs) have emerged as powerful tools for processing relational data in applications. However, GNNs suffer from the problem of oversmoothing, the property that the features of all nodes exponentially converge to the…

Machine Learning · Statistics 2025-05-22 Bastian Epping , Alexandre René , Moritz Helias , Michael T. Schaub

A significant generalization of the Erd\"os-R\'enyi random graph model is an `inhomogeneous' random graph where the edge probabilities vary according to vertex types. We identify the threshold value for this random graph with a finite…

Probability · Mathematics 2024-11-06 Hamin Jung

A common model for social networks are Geometric Inhomogeneous Random Graphs (GIRGs), in which vertices draw a random position in some latent geometric space, and the probability of two vertices forming an edge depends on their geometric…

Social and Information Networks · Computer Science 2025-06-25 Marc Kaufmann , Johannes Lengler , Ulysse Schaller , Konstantin Sturm

A connected graph $G$ with at least $2m + 2n + 2$ vertices which contains a perfect matching is $E(m, n)$-{\it extendable}, if for any two sets of disjoint independent edges $M$ and $N$ with $|M| = m$ and $|N|= n$, there is a perfect…

Combinatorics · Mathematics 2023-06-22 Hongliang Lu , Qinglin Yu

A graphon is a limiting object used to describe the behaviour of large networks through a function that captures the probability of edge formation between nodes. Although the merits of graphons to describe large and unlabelled networks are…

Methodology · Statistics 2024-08-23 Charles Dufour , Sofia C. Olhede

We improve the best known lower bounds on the exponential behavior of the maximum of the number of connected sets, $N(G)$, and dominating connected sets, $N_{dom}(G)$, for regular graphs. These lower bounds are improved by constructing a…

Combinatorics · Mathematics 2024-09-27 Stijn Cambie , Jan Goedgebeur , Jorik Jooken

Given a connected graph $G$ with some subset of its vertices excited and a fixed target vertex, in the geodesic-biased random walk on $G$, a random walker moves as follows: from an unexcited vertex, she moves to a uniformly random…

Probability · Mathematics 2019-09-13 Mikhail Beliayeu , Petr Chmel , Bhargav Narayanan , Jan Petr

Graph embedding has recently gained momentum in the research community, in particular after the introduction of random walk and neural network based approaches. However, most of the embedding approaches focus on representing the local…

Machine Learning · Computer Science 2020-02-19 Joerg Schloetterer , Martin Wehking , Fatemeh Salehi Rizi , Michael Granitzer

Constructing a spanning tree of a graph is one of the most basic tasks in graph theory. We consider this problem in the setting of local algorithms: one wants to quickly determine whether a given edge $e$ is in a specific spanning tree,…

Data Structures and Algorithms · Computer Science 2021-04-28 Reut Levi , Dana Ron , Ronitt Rubinfeld

Graph Neural Networks (GNNs) have achieved a lot of success with graph-structured data. However, it is observed that the performance of GNNs does not improve (or even worsen) as the number of layers increases. This effect has known as…

Machine Learning · Computer Science 2023-01-10 Yeskendir Koishekenov

Real-world graphs, such as social networks, financial transactions, and recommendation systems, often demonstrate dynamic behavior. This phenomenon, known as graph stream, involves the dynamic changes of nodes and the emergence and…

Machine Learning · Computer Science 2023-05-16 Yanping Zheng , Zhewei Wei , Jiajun Liu

Limiting distributions are derived for the sparse connected components that are present when a random graph on $n$ vertices has approximately $\half n$ edges. In particular, we show that such a graph consists entirely of trees, unicyclic…

Probability · Mathematics 2008-02-03 Svante Janson , Donald E. Knuth , Tomasz Łuczak , Boris Pittel

Consider a family $\mathcal{T}$ of 3-connected graphs of moderate growth, and let $\mathcal{G}$ be the class of graphs whose 3-connected components are graphs in $\mathcal{T}$. We present a general framework for analyzing such graphs…

Combinatorics · Mathematics 2009-07-03 Omer Gimenez , Marc Noy , Juanjo Rue

A simple topological graph $G$ is a graph drawn in the plane so that any pair of edges have at most one point in common, which is either an endpoint or a proper crossing. $G$ is called saturated if no further edge can be added without…

Combinatorics · Mathematics 2015-01-30 Jan Kynčl , János Pach , Radoš Radoičić , Géza Tóth
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