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Graph is an important data representation which appears in a wide diversity of real-world scenarios. Effective graph analytics provides users a deeper understanding of what is behind the data, and thus can benefit a lot of useful…

Artificial Intelligence · Computer Science 2018-02-05 Hongyun Cai , Vincent W. Zheng , Kevin Chen-Chuan Chang

Traditional representations of graphs and their duals suggest the requirement that the dual vertices be placed inside their corresponding primal faces, and the edges of the dual graph cross only their corresponding primal edges. We consider…

Computational Geometry · Computer Science 2007-05-23 C. Erten , S. G. Kobourov

Simultaneous embedding is concerned with simultaneously representing a series of graphs sharing some or all vertices. This forms the basis for the visualization of dynamic graphs and thus is an important field of research. Recently there…

Data Structures and Algorithms · Computer Science 2015-06-22 Thomas Bläsius , Stephen G. Kobourov , Ignaz Rutter

The central theorem of topological graph theory states that the graph minor relation is a well-quasi-order on graphs. It has far-reaching consequences, in particular in the study of graph structures and the design of (parameterized)…

Computational Geometry · Computer Science 2025-12-04 Corentin Lunel , Clément Maria

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

We investigate the structure of isometric subgraphs of hypercubes (i.e., partial cubes) which do not contain finite convex subgraphs contractible to the 3-cube minus one vertex $Q^-_3$ (here contraction means contracting the edges…

Combinatorics · Mathematics 2019-08-26 Victor Chepoi , Kolja Knauer , Tilen Marc

An ordinary voltage graph embedding of a graph in a surface encodes a certain kind of highly symmetric covering space of that surface. Given an ordinary voltage graph embedding of a graph $G$ in a surface with voltage group $A$ and a…

Combinatorics · Mathematics 2016-11-10 Steven Schluchter

Partial duality generalizes the fundamental concept of the geometric dual of an embedded graph. A partial dual is obtained by forming the geometric dual with respect to only a subset of edges. While geometric duality preserves the genus of…

Combinatorics · Mathematics 2013-11-18 Iain Moffatt

In this paper, we analyze embeddings of grid graphs on orientable surfaces. We determine the genus of a large class of k-dimensional grid graphs and effective two-sided bounds for the genus of any 3-dimensional grid graph, both in terms of…

Combinatorics · Mathematics 2022-04-20 Christian Millichap , Fabian Salinas

We introduce a categorical formalism for rewriting surface-embedded graphs. Such graphs can represent string diagrams in a non-symmetric setting where we guarantee that the wires do not intersect each other. The main technical novelty is a…

Logic in Computer Science · Computer Science 2023-08-01 Malin Altenmüller , Ross Duncan

The study of graph drawings on 2-surfaces is an active area of mathematical research. Our main results are criteria for integer and modulo 2 embeddability of graphs to surfaces.

Combinatorics · Mathematics 2021-11-17 Arthur Bikeev

We extend the notion of graph homomorphism to cellularly embedded graphs (maps) by designing operations on vertices and edges that respect the surface topology; we thus obtain the first definition of map homomorphism that preserves both the…

Combinatorics · Mathematics 2023-05-08 Delia Garijo , Andrew Goodall , Lluís Vena

An isometric embedding of a graph into a metric space is an embedding of the vertices such that the smallest number of edges connecting any two vertices equals to the distance in the metric space between the images. In this paper, we study…

Metric Geometry · Mathematics 2018-04-20 Shiquan Ren

A graph drawing in the plane is called an almost embedding if the images of any two non-adjacent simplices (i.e. vertices or edges) are disjoint. Almost embeddings (more precisely, their higher-dimensional analogues) naturally appear in…

Geometric Topology · Mathematics 2026-03-10 E. Alkin , A. Miroshnikov , A. Skopenkov

Neural embeddings have been used with great success in Natural Language Processing (NLP). They provide compact representations that encapsulate word similarity and attain state-of-the-art performance in a range of linguistic tasks. The…

Machine Learning · Statistics 2018-09-20 Benjamin Paul Chamberlain , James Clough , Marc Peter Deisenroth

Consider the collection of edge bicolorings of a graph that is cellularly embedded on an orientable surface. In this work, we count the number of equivalence classes of such colorings under two relations: reversing colors around a face and…

Geometric Topology · Mathematics 2018-02-13 Oliver T. Dasbach , Heather M. Russell

We present a form of algebraic reasoning for computational objects which are expressed as graphs. Edges describe the flow of data between primitive operations which are represented by vertices. These graphs have an interface made of…

Logic in Computer Science · Computer Science 2010-07-23 Lucas Dixon , Ross Duncan , Aleks Kissinger

We show how arbitrary unit cells of periodic materials can be represented as graphs whose nodes represent atoms and whose weighted edges represent tunneling connections between atoms. Further, we present methods to calculate the band…

Other Condensed Matter · Physics 2024-12-20 R. Gerstner

A signed graph (SG) is a graph where edges carry sign information attached to it. The sign of a network can be positive, negative, or neutral. A signed network is ubiquitous in a real-world network like social networks, citation networks,…

Social and Information Networks · Computer Science 2024-09-09 Shrabani Ghosh

Representing graphs as sets of node embeddings in certain curved Riemannian manifolds has recently gained momentum in machine learning due to their desirable geometric inductive biases, e.g., hierarchical structures benefit from hyperbolic…

Machine Learning · Computer Science 2020-06-09 Calin Cruceru , Gary Bécigneul , Octavian-Eugen Ganea