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We present a concept called the branch-depth of a connectivity function, that generalizes the tree-depth of graphs. Then we prove two theorems showing that this concept aligns closely with the notions of tree-depth and shrub-depth of graphs…

Combinatorics · Mathematics 2020-11-05 Matt DeVos , O-joung Kwon , Sang-il Oum

Given a graph $ G $ with $ n $ vertices and a set $ S $ of $ n $ points in the plane, a point-set embedding of $ G $ on $ S $ is a planar drawing such that each vertex of $ G $ is mapped to a distinct point of $ S $. A straight-line…

Computational Geometry · Computer Science 2017-08-07 Hamid Hoorfar , Alireza Bagheri

Graph Neural Networks (GNNs) have emerged as a flexible and powerful approach for learning over graphs. Despite this success, existing GNNs are constrained by their local message-passing architecture and are provably limited in their…

Machine Learning · Computer Science 2021-10-29 Rajat Talak , Siyi Hu , Lisa Peng , Luca Carlone

We here investigate on the complexity of computing the \emph{tree-length} and the \emph{tree-breadth} of any graph $G$, that are respectively the best possible upper-bounds on the diameter and the radius of the bags in a tree decomposition…

Computational Complexity · Computer Science 2016-01-11 Guillaume Ducoffe , Sylvain Legay , Nicolas Nisse

We introduce new distance measures for comparing straight-line embedded graphs based on the Fr\'echet distance and the weak Fr\'echet distance. These graph distances are defined using continuous mappings and thus take the combinatorial…

Computational Geometry · Computer Science 2019-09-12 Hugo A. Akitaya , Maike Buchin , Bernhard Kilgus , Stef Sijben , Carola Wenk

Graph representation learning is a fast-growing field where one of the main objectives is to generate meaningful representations of graphs in lower-dimensional spaces. The learned embeddings have been successfully applied to perform various…

Machine Learning · Computer Science 2021-12-21 Md. Khaledur Rahman , Ariful Azad

Graph embeddings have become a key and widely used technique within the field of graph mining, proving to be successful across a broad range of domains including social, citation, transportation and biological. Graph embedding techniques…

Machine Learning · Computer Science 2018-06-21 Stephen Bonner , Ibad Kureshi , John Brennan , Georgios Theodoropoulos , Andrew Stephen McGough , Boguslaw Obara

Given a collection of planar graphs $G_1,\dots,G_k$ on the same set $V$ of $n$ vertices, the simultaneous geometric embedding (with mapping) problem, or simply $k$-SGE, is to find a set $P$ of $n$ points in the plane and a bijection $\phi:…

Computational Geometry · Computer Science 2015-05-08 Jean Cardinal , Vincent Kusters

Due to their flexibility to represent almost any kind of relational data, graph-based models have enjoyed a tremendous success over the past decades. While graphs are inherently only combinatorial objects, however, many prominent analysis…

Social and Information Networks · Computer Science 2024-03-27 Michaël Fanuel , Antoine Aspeel , Michael T. Schaub , Jean-Charles Delvenne

Graph embedding has become an increasingly important technique for analyzing graph-structured data. By representing nodes in a graph as vectors in a low-dimensional space, graph embedding enables efficient graph processing and analysis…

Machine Learning · Computer Science 2023-09-13 Hamidreza Lotfalizadeh , Mohammad Al Hasan

The problem of computing all maximal induced subgraphs of a graph G that have a graph property P, also called the maximal P-subgraphs problem, is considered. This problem is studied for hereditary, connected-hereditary and rooted-hereditary…

Data Structures and Algorithms · Computer Science 2007-05-23 Sara Cohen , Yehoshua Sagiv

The Induced Graph Matching problem asks to find k disjoint induced subgraphs isomorphic to a given graph H in a given graph G such that there are no edges between vertices of different subgraphs. This problem generalizes the classical…

Discrete Mathematics · Computer Science 2014-02-11 Danny Hermelin , Matthias Mnich , Erik Jan van Leeuwen

In graph representation learning, it is important that the complex geometric structure of the input graph, e.g. hidden relations among nodes, is well captured in embedding space. However, standard Euclidean embedding spaces have a limited…

Machine Learning · Computer Science 2023-07-11 Tuc Nguyen-Van , Dung D. Le , The-Anh Ta

Computing a minimum-area planar straight-line drawing of a graph is known to be NP-hard for planar graphs, even when restricted to outerplanar graphs. However, the complexity question is open for trees. Only a few hardness results are known…

Computational Geometry · Computer Science 2017-09-01 Therese Biedl , Debajyoti Mondal

A rectangle visibility representation (RVR) of a graph consists of an assignment of axis-aligned rectangles to vertices such that for every edge there exists a horizontal or vertical line of sight between the rectangles assigned to its…

Computational Geometry · Computer Science 2019-09-04 Therese Biedl , Giuseppe Liotta , Fabrizio Montecchiani

Let H be a graph, and let C_H(G) be the number of (subgraph isomorphic) copies of H contained in a graph G. We investigate the fundamental problem of estimating C_H(G). Previous results cover only a few specific instances of this general…

Data Structures and Algorithms · Computer Science 2019-02-20 Martin Furer , Shiva Prasad Kasiviswanathan

Heterogeneous graphs (HGs) also known as heterogeneous information networks have become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn representations in a lower-dimension space while preserving the…

Social and Information Networks · Computer Science 2020-12-02 Xiao Wang , Deyu Bo , Chuan Shi , Shaohua Fan , Yanfang Ye , Philip S. Yu

Visual rendering of graphs is a key task in the mapping of complex network data. Although most graph drawing algorithms emphasize aesthetic appeal, certain applications such as travel-time maps place more importance on visualization of…

Machine Learning · Statistics 2013-02-06 Brian Baingana , Georgios B. Giannakis

Graph product structure theory expresses certain graphs as subgraphs of the strong product of much simpler graphs. In particular, an elegant formulation for the corresponding structural theorems involves the strong product of a path and of…

Data Structures and Algorithms · Computer Science 2022-04-26 Michael A. Bekos , Giordano Da Lozzo , Petr Hliněný , Michael Kaufmann

We consider homomorphisms of signed graphs from a computational perspective. In particular, we study the list homomorphism problem seeking a homomorphism of an input signed graph $(G,\sigma)$, equipped with lists $L(v) \subseteq V(H), v \in…

Combinatorics · Mathematics 2023-05-30 Jan Bok , Richard Brewster , Tomás Feder , Pavol Hell , Nikola Jedličková
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