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Graphs are nowadays ubiquitous in the fields of signal processing and machine learning. As a tool used to express relationships between objects, graphs can be deployed to various ends: I) clustering of vertices, II) semi-supervised…

Machine Learning · Computer Science 2020-07-17 Carlos Lassance , Vincent Gripon , Gonzalo Mateos

The graph structure is a commonly used data storage mode, and it turns out that the low-dimensional embedded representation of nodes in the graph is extremely useful in various typical tasks, such as node classification, link prediction ,…

Social and Information Networks · Computer Science 2020-08-03 Xing Li , Wei Wei , Xiangnan Feng , Xue Liu , Zhiming Zheng

Given an underlying undirected simple graph, we consider the set of all acyclic orientations of its edges. Each of these orientations induces a partial order on the vertices of our graph and, therefore, we can count the number of linear…

Combinatorics · Mathematics 2015-02-17 Benjamin Iriarte Giraldo

A (possibly denerate) drawing of a graph $G$ in the plane is approximable by an embedding if it can be turned into an embedding by an arbitrarily small perturbation. We show that testing, whether a straight-line drawing of a planar graph…

Computational Geometry · Computer Science 2017-05-09 Radoslav Fulek

This paper is based on a series of talks given at the Patejdlovka Enumeration Workshop held in the Czech Republic in November 2007. The topics covered are as follows. The graph polynomial, Tutte-Grothendieck invariants, an overview of…

Combinatorics · Mathematics 2008-07-01 Andrew Goodall

The simulation of the physical movement of multi-body systems at an atomistic level, with forces calculated from a quantum mechanical description of the electrons, motivates a graph partitioning problem studied in this article. Several…

To directed graphs with unique sink and source we associate a noncommutative associative alsgebra and a polynomial over this algebra. Edges of the graph correspond to pseudo-roots of the polynomial. We give a sufficient condition when…

Quantum Algebra · Mathematics 2009-11-11 Israel Gelfand , Sergei Gelfand , Vladimir Retakh , Robert Lee Wilson

There are many variations on partition functions for graph homomorphisms or colorings. The case considered here is a counting or hard constraint problem in which the range or color graph carries a free and vertex transitive Abelian group…

Combinatorics · Mathematics 2012-04-06 Eric Babson , Matthias Beck

Graphs are ubiquitous in encoding relational information of real-world objects in many domains. Graph generation, whose purpose is to generate new graphs from a distribution similar to the observed graphs, has received increasing attention…

Machine Learning · Computer Science 2022-12-08 Yanqiao Zhu , Yuanqi Du , Yinkai Wang , Yichen Xu , Jieyu Zhang , Qiang Liu , Shu Wu

For a class $\mathcal{G}$ of graphs, the objective of \textsc{Subgraph Complementation to} $\mathcal{G}$ is to find whether there exists a subset $S$ of vertices of the input graph $G$ such that modifying $G$ by complementing the subgraph…

Data Structures and Algorithms · Computer Science 2023-03-29 Dhanyamol Antony , Sagartanu Pal , R. B. Sandeep

Various simplicial complexes can be associated with a graph. Box complexes form an important families of such simplicial complexes and are especially useful for providing lower bounds on the chromatic number of the graph via some of their…

Combinatorics · Mathematics 2024-01-05 Hamid Reza Daneshpajouh , Frédéric Meunier

We show how graph neural networks can be used to solve the canonical graph coloring problem. We frame graph coloring as a multi-class node classification problem and utilize an unsupervised training strategy based on the statistical physics…

Machine Learning · Computer Science 2022-11-28 Martin J. A. Schuetz , J. Kyle Brubaker , Zhihuai Zhu , Helmut G. Katzgraber

Tiered graph autoencoders provide the architecture and mechanisms for learning tiered latent representations and latent spaces for molecular graphs that explicitly represent and utilize groups (e.g., functional groups). This enables the…

Machine Learning · Computer Science 2021-07-02 Daniel T. Chang

Learning graphs from sets of nodal observations represents a prominent problem formally known as graph topology inference. However, current approaches are limited by typically focusing on inferring single networks, and they assume that…

Social and Information Networks · Computer Science 2021-11-17 Samuel Rey , Andrei Buciulea , Madeline Navarro , Santiago Segarra , Antonio G. Marques

A book Chapter consisting of some of the main areas of research in graph theory applied to physics. It includes graphs in condensed matter theory, such as the tight-binding and the Hubbard model. It follows the study of graph theory and…

Mathematical Physics · Physics 2013-06-19 Ernesto Estrada

In a balanced graph decomposition, every vertex of the host graph appears in the same number of blocks. We propose the use of colored loops as a framework for unifying various other types of local balance conditions in graph decompositions.…

Combinatorics · Mathematics 2020-02-21 Flora C. Bowditch , Peter J. Dukes

A map is a connected topological graph cellularly embedded in a surface and a complete map is a cellularly embedded complete graph in a surface. In this paper, all automorphisms of complete maps of order n are determined by permutations on…

General Mathematics · Mathematics 2009-09-29 Linfan Mao , Yanpei Liu , Feng Tian

In a recent paper, we studied the interaction between the automorphism group of a graph and its Tutte polynomial. More precisely, we proved that certain symmetries of graphs are clearly reflected by their Tutte polynomials. The purpose of…

Combinatorics · Mathematics 2018-02-26 Chbili Nafaa

In the past decades for more and more graph classes the Graph Isomorphism Problem was shown to be solvable in polynomial time. An interesting family of graph classes arises from intersection graphs of geometric objects. In this work we show…

Data Structures and Algorithms · Computer Science 2016-06-23 Daniel Neuen

We propose a novel node embedding of directed graphs to statistical manifolds, which is based on a global minimization of pairwise relative entropy and graph geodesics in a non-linear way. Each node is encoded with a probability density…

Machine Learning · Computer Science 2020-02-07 Thorben Funke , Tian Guo , Alen Lancic , Nino Antulov-Fantulin