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Related papers: Recipes for Edge-Transitive Tetravalent Graphs

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A complete list of all connected arc-transitive asymmetric digraphs of in-valence and out-valence 2 on up to 1000 vertices is presented. As a byproduct, a complete list of all connected 4-valent graphs admitting a half-arc-transitive group…

Combinatorics · Mathematics 2013-11-11 Primoz Potocnik , Pablo Spiga , Gabriel Verret

In this paper, we introduce a family of tetravalent graphs called propeller graphs, denoted by $Pr_{n}(b,c,d)$. We then produce three infinite subfamilies and one finite subfamily of arc-transitive propeller graphs, and show that all such…

Combinatorics · Mathematics 2016-01-05 Matthew C. Sterns

In this paper, we give a characterization for a class of edge-transitive Cayley graphs, and provide methods for constructing Cayley graphs with certain symmetry properties. Also this study leads to construct and characterise a new family of…

Group Theory · Mathematics 2016-08-30 Lei Wang

A graph is called cubic and tetravalent if all of its vertices have valency 3 and 4, respectively. It is called vertex-transitive and arc-transitive if its automorphism group acts transitively on its vertex-set and on its arc- set,…

Combinatorics · Mathematics 2012-01-26 Primoz Potocnik , Pablo Spiga , Gabriel Verret

In this paper, we study edge-transitive surfaces, i.e. triangulated 2-dimensional manifolds whose automorphism groups act transitively on the edges of these triangulated surfaces. We show that there exist four types of edge-transitive…

Combinatorics · Mathematics 2025-11-12 Reymond Akpanya

This paper presents a phenomenon which sometimes occurs in tetravalent bipartite locally dart-transitive graphs, called a Base Graph -- Connection Graph dissection. In this dissection, each white vertex is split into two vertices of valence…

Combinatorics · Mathematics 2020-04-07 Gabriel Verret , Primož Potočnik , Steve Wilson

It has long been known that there exist finite connected tetravalent arc-transitive graphs with arbitrarily large vertex-stabilisers. However, beside a well known family of exceptional graphs, related to the lexicographic product of a cycle…

Combinatorics · Mathematics 2010-10-14 Primoz Potocnik , Pablo Spiga , Gabriel Verret

A graph is said to be edge-transitive if its automorphism group acts transitively on its edges. It is known that edge-transitive graphs are either vertex-transitive or bipartite. In this paper we present a complete classification of all…

Combinatorics · Mathematics 2019-11-13 Heather A. Newman , Hector Miranda , Darren A. Narayan

Graph, as an important data representation, is ubiquitous in many real world applications ranging from social network analysis to biology. How to correctly and effectively learn and extract information from graph is essential for a large…

Machine Learning · Computer Science 2020-10-27 Xiaodong Jiang , Ronghang Zhu , Pengsheng Ji , Sheng Li

Tetravalent graphs admitting a half-arc-transitive subgroup of automorphisms, that is a subgroup acting transitively on its vertices and its edges but not on its arcs, are investigated. One of the most fruitful approaches for the study of…

Combinatorics · Mathematics 2018-01-29 Alejandra Ramos Rivera , Primož Šparl

This paper presents a characterization of edge-transitive graphs which are four regular and have girth four. This class consists of four infinite families plus four exceptional graphs.

Combinatorics · Mathematics 2015-11-24 Tomas Boothby , Matt DeVos

This paper reviews graph convolutional neural networks (GCNNs) through the lens of edge-variant graph filters. The edge-variant graph filter is a finite order, linear, and local recursion that allows each node, in each iteration, to weigh…

Machine Learning · Computer Science 2019-03-05 Elvin Isufi , Fernando Gama , Alejandro Ribeiro

Compared to sequential learning models, graph-based neural networks exhibit excellent ability in capturing global information and have been used for semi-supervised learning tasks. Most Graph Convolutional Networks are designed with the…

Computation and Language · Computer Science 2022-04-12 Kunze Wang , Soyeon Caren Han , Siqu Long , Josiah Poon

Building on earlier work of Biggs, James, Wilson and the author, and using the Graver-Watkins description of the 14 classes of edge-transitive maps, we complete the classification of the edge-transitive embeddings of complete graphs.

Combinatorics · Mathematics 2019-08-06 Gareth A. Jones

A typical census of 3-manifolds contains all manifolds (under various constraints) that can be triangulated with at most n tetrahedra. Al- though censuses are useful resources for mathematicians, constructing them is difficult: the best…

Geometric Topology · Mathematics 2019-09-10 Benjamin A. Burton , William Pettersson

Vertex connectivity and edge connectivity are fundamental concepts in graph theory that have been widely studied from both structural and algorithmic perspectives. The focus of this paper is on computing these two parameters for graphs…

Data Structures and Algorithms · Computer Science 2025-10-14 Therese Biedl , Prosenjit Bose , Karthik Murali

In this paper, we propose a new type of graph, denoted as "embedded-graph", and its theory, which employs a distributed representation to describe the relations on the graph edges. Embedded-graphs can express linguistic and complicated…

Discrete Mathematics · Computer Science 2017-09-15 Atsushi Yokoyama

In order to complete (and generalize) results of Gardiner and Praeger on 4-valent symmetric graphs (European J. Combin, 15 (1994)) we apply the method of lifting automorphisms in the context of elementary-abelian covering projections. In…

Combinatorics · Mathematics 2017-08-01 Boštjan Kuzman , Aleksander Malnič , Primož Potočnik

Graphlets are defined as k-node connected induced subgraph patterns. For an undirected graph, 3-node graphlets include close triangle and open triangle. When k = 4, there are six types of graphlets, e.g., tailed-triangle and clique are two…

Machine Learning · Computer Science 2018-10-09 Xutong Liu , Yu-Zhen Janice Chen , John C. S. Lui , Konstantin Avrachenkov

Graph embedding techniques allow to learn high-quality feature vectors from graph structures and are useful in a variety of tasks, from node classification to clustering. Existing approaches have only focused on learning feature vectors for…

Artificial Intelligence · Computer Science 2019-05-29 Valeria Fionda , Giuseppe Pirró
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