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In this paper, we introduce a generalization of graphlets to heterogeneous networks called typed graphlets. Informally, typed graphlets are small typed induced subgraphs. Typed graphlets generalize graphlets to rich heterogeneous networks…

Social and Information Networks · Computer Science 2020-10-28 Ryan A. Rossi , Nesreen K. Ahmed , Aldo Carranza , David Arbour , Anup Rao , Sungchul Kim , Eunyee Koh

We prove well-posedness for very general linear wave- and diffusion equations on compact or non-compact metric graphs allowing various different conditions in the vertices. More precisely, using the theory of strongly continuous operator…

Analysis of PDEs · Mathematics 2020-06-08 Klaus-Jochen Engel , Marjeta Kramar Fijavž

We study the detection and the reconstruction of a large very dense subgraph in a social graph with $n$ nodes and $m$ edges given as a stream of edges, when the graph follows a power law degree distribution, in the regime when $m=O(n. \log…

Data Structures and Algorithms · Computer Science 2023-06-22 Claire Mathieu , Michel de Rougemont

The graphicality problem -- whether or not a sequence of integers can be used to create a simple graph -- is a key question in network theory and combinatorics, with many important practical applications. In this work, we study the…

Disordered Systems and Neural Networks · Physics 2026-01-01 Pietro Valigi , M. Ángeles Serrano , Claudio Castellano , Lorenzo Cirigliano

We have a set of processors (or agents) and a set of graph networks defined over some vertex set. Each processor can access a subset of the graph networks. Each processor has a demand specified as a pair of vertices $<u, v>$, along with a…

Data Structures and Algorithms · Computer Science 2012-10-08 Venkatesan T. Chakaravarthy , Sambuddha Roy , Yogish Sabharwal

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks. Graph neural networks (GNNs) have achieved great success in representation learning on graphs, facilitating various…

Machine Learning · Computer Science 2025-02-27 Zhimeng Guo , Teng Xiao , Zongyu Wu , Charu Aggarwal , Hui Liu , Suhang Wang

Graph generation generally aims to create new graphs that closely align with a specific graph distribution. Existing works often implicitly capture this distribution through the optimization of generators, potentially overlooking the…

Machine Learning · Computer Science 2024-07-19 Song Wang , Zhen Tan , Xinyu Zhao , Tianlong Chen , Huan Liu , Jundong Li

Bidirected graphs are a common generalisation of directed graphs where arcs can also be incoming to both their incident nodes, or outgoing from both their incident nodes. Such arcs allow a walk to change direction. Some algorithms can…

Data Structures and Algorithms · Computer Science 2026-05-14 Sebastian Schmidt , Juha Harviainen , Corentin Moumard , Aleksandr Politov , Francisco Sena , Alexandru I. Tomescu

Hypergraphs have emerged as a powerful modeling framework to represent systems with multiway interactions, that is systems where interactions may involve an arbitrary number of agents. Here we explore the properties of real-world…

Social and Information Networks · Computer Science 2023-07-11 Timothy LaRock , Renaud Lambiotte

We investigate the structure of graphs of twin-width at most $1$, and obtain the following results: - Graphs of twin-width at most $1$ are permutation graphs. In particular they have an intersection model and a linear structure. - There is…

Discrete Mathematics · Computer Science 2025-01-03 Jungho Ahn , Hugo Jacob , Noleen Köhler , Christophe Paul , Amadeus Reinald , Sebastian Wiederrecht

Graphs are widely used as a popular representation of the network structure of connected data. Graph data can be found in a broad spectrum of application domains such as social systems, ecosystems, biological networks, knowledge graphs, and…

Machine Learning · Computer Science 2021-05-04 Feng Xia , Ke Sun , Shuo Yu , Abdul Aziz , Liangtian Wan , Shirui Pan , Huan Liu

Given a dynamic network, where edges appear and disappear over time, we are interested in finding sets of edges that have similar temporal behavior and form a dense subgraph. Formally, we define the problem as the enumeration of the maximal…

Social and Information Networks · Computer Science 2021-03-02 Giulia Preti , Polina Rozenshtein , Aristides Gionis , Yannis Velegrakis

Directed graphs have long been used to gain understanding of the structure of semigroups, and recently the structure of directed graph semigroups has been investigated resulting in a characterization theorem and an analog of Fruct's…

Combinatorics · Mathematics 2015-06-09 Tien Chih , Demitri Plessas

The burning and forcing processes are both instances of propagation processes on graphs that are commonly used to model real-world spreading phenomena. The contribution of this paper is two-fold. We first establish a connection between…

Combinatorics · Mathematics 2026-02-16 Aida Abiad , Pax Mallee

It is challenging for generative models to learn a distribution over graphs because of the lack of permutation invariance: nodes may be ordered arbitrarily across graphs, and standard graph alignment is combinatorial and notoriously…

Social and Information Networks · Computer Science 2023-01-27 Kimia Shayestehfard , Dana Brooks , Stratis Ioannidis

A subgraph is constructed by using a subset of vertices and edges of a given graph. There exist many graph properties that are hereditary for subgraphs. Hence, researchers from different communities have paid a great deal of attention in…

Combinatorics · Mathematics 2023-06-06 Kai Siong Yow , Ningyi Liao , Siqiang Luo , Reynold Cheng , Chenhao Ma , Xiaolin Han

An intuitive property of a random graph is that its subgraphs should also appear randomly distributed. We consider graphs whose subgraph densities exactly match their expected values. We call graphs with this property for all subgraphs with…

Combinatorics · Mathematics 2020-03-10 Sebastian Jeon , Tanya Khovanova

Data analysts commonly utilize statistics to summarize large datasets. While it is often sufficient to explore only the summary statistics of a dataset (e.g., min/mean/max), Anscombe's Quartet demonstrates how such statistics can be…

Computational Geometry · Computer Science 2019-11-06 Hang Chen , Vahan Huroyan , Utkarsh Soni , Yafeng Lu , Ross Maciejewski , Stephen Kobourov

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

Let $G$ be a finite group. The order supergraph of $G$ is the graph with vertex set $G$, and two distinct vertices $x,y$ are adjacent if $o(x)\mid o(y)$ or $o(y)\mid o(x)$. The enhanced power graph of $G$ is the graph whose vertex set is…

Combinatorics · Mathematics 2021-04-29 Xuanlong Ma , Liangliang Zhai