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In the field of graph signal processing (GSP), directed graphs present a particular challenge for the "standard approaches" of GSP to due to their asymmetric nature. The presence of negative- or complex-weight directed edges, a graphical…

Signal Processing · Electrical Eng. & Systems 2020-03-03 Kevin Schultz , Marisel Villafane-Delgado

We introduce a general class of algorithms and supply a number of general results useful for analysing these algorithms when applied to regular graphs of large girth. As a result, we can transfer a number of results proved for random…

Combinatorics · Mathematics 2017-03-06 Carlos Hoppen , Nicholas Wormald

Invariants withstand transformations and, therefore, represent the essence of objects or phenomena. In mathematics, transformations often constitute a group action. Since the 19th century, studying the structure of various types of…

Symbolic Computation · Computer Science 2024-12-19 Irina A. Kogan

Within biology, it is of interest to construct DNA complexes of a certain shape. These complexes can be represented through graph theory, using edges to model strands of DNA joined at junctions, represented by vertices. Because guided…

Vertex splitting is a graph modification operation in which a vertex is replaced by multiple vertices such that the union of their neighborhoods equals the neighborhood of the original vertex. We introduce and study vertex splitting as a…

Computational Complexity · Computer Science 2026-02-05 Faisal N. Abu-Khzam , Dipayan Chakraborty , Lucas Isenmann , Nacim Oijid

A common choice for the evolution of the knotted graphs in loop quantum gravity is to use the Pachner moves, adapted to graphs from their dual triangulations. Here, we show that the natural way to consistently use these moves is on framed…

General Relativity and Quantum Cosmology · Physics 2024-06-06 Daniel Cartin

A cornerstone of geometric reconstruction, rotation averaging seeks the set of absolute rotations that optimally explains a set of measured relative orientations between them. In addition to being an integral part of bundle adjustment and…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Gabriel Moreira , Manuel Marques , João Paulo Costeira

We consider the problem of transforming a given graph $G_s$ into a desired graph $G_t$ by applying a minimum number primitives from a particular set of local graph transformation primitives. These primitives are local in the sense that each…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-11 Christian Scheideler , Alexander Setzer

Let $G=(V, E)$ be a graph where $V$ and $E$ are the vertex and edge sets, respectively. For two disjoint subsets $A$ and $B$ of $V$, we say $A$ \emph{dominates} $B$ if every vertex of $B$ is adjacent to at least one vertex of $A$. A vertex…

Combinatorics · Mathematics 2023-10-09 Subhabrata Paul , Kamal Santra

In graph signal processing, one of the most important subjects is the study of filters, i.e., linear transformations that capture relations between graph signals. One of the most important families of filters is the space of shift invariant…

Signal Processing · Electrical Eng. & Systems 2022-09-29 Feng Ji , See Hian Lee , Wee Peng Tay

We prove that any non-amenable Cayley graph admits a factor of IID perfect matching. We also show that any connected d-regular vertex tran- sitive graph admits a perfect matching. The two results together imply that every Cayley graph…

Combinatorics · Mathematics 2012-11-13 Endre Csoka , Gabor Lippner

Deep generative models (DGMs) have recently demonstrated remarkable success in capturing complex probability distributions over graphs. Although their excellent performance is attributed to powerful and scalable deep neural networks, it is,…

Machine Learning · Computer Science 2025-03-18 Milan Papež , Martin Rektoris , Václav Šmídl , Tomáš Pevný

In this paper we study the algebra of graph invariants, focusing mainly on the invariants of simple graphs. All other invariants, such as sorted eigenvalues, degree sequences and canonical permutations, belong to this algebra. In fact,…

Combinatorics · Mathematics 2008-01-30 Tomi Mikkonen , Xavier Buchwalder

The maximum genus $\gamma_M(G)$ of a graph G is the largest genus of an orientable surface into which G has a cellular embedding. Combinatorially, it coincides with the maximum number of disjoint pairs of adjacent edges of G whose removal…

Combinatorics · Mathematics 2015-01-30 Michal Kotrbcik , Martin Skoviera

Graph neural networks (GNNs) extends the functionality of traditional neural networks to graph-structured data. Similar to CNNs, an optimized design of graph convolution and pooling is key to success. Borrowing ideas from physics, we…

Machine Learning · Computer Science 2022-01-12 Zheng Ma , Junyu Xuan , Yu Guang Wang , Ming Li , Pietro Lio

For a graph invariant $\pi$, the Contraction($\pi$) problem consists in, given a graph $G$ and two positive integers $k,d$, deciding whether one can contract at most $k$ edges of $G$ to obtain a graph in which $\pi$ has dropped by at least…

Data Structures and Algorithms · Computer Science 2021-03-23 Paloma T. Lima , Vinicius F. dos Santos , Ignasi Sau , Uéverton S. Souza

We follow up on previous work which found that commonly used graph evolution moves lead to conserved quantities that can be expressed in terms of the braiding of the graph in its embedding space. We study non-embedded graphs under three…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Fotini Markopoulou , Isabeau Prémont-Schwarz

Graphs are fundamental data structures which concisely capture the relational structure in many important real-world domains, such as knowledge graphs, physical and social interactions, language, and chemistry. Here we introduce a powerful…

Machine Learning · Computer Science 2018-03-12 Yujia Li , Oriol Vinyals , Chris Dyer , Razvan Pascanu , Peter Battaglia

A permutation graph $G_\pi$ is a simple graph with vertices corresponding to the elements of $\pi$ and an edge between $i$ and $j$ when $i$ and $j$ are inverted in $\pi$. A set of vertices $D$ is said to dominate a graph $G$ when every…

Exploiting symmetries and invariance in data is a powerful, yet not fully exploited, way to achieve better generalisation with more efficiency. In this paper, we introduce two graph network architectures that are equivariant to several…

Machine Learning · Computer Science 2021-06-01 Francesco Farina , Emma Slade