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Using connections to random matrix theory and orthogonal polynomials, we develop a framework for obtaining explicit closed-form formulae for the number, $\mathscr{N}_{g}(2\nu,j)$, of connected $2\nu$-valent labeled graphs with $j$ vertices…

Combinatorics · Mathematics 2025-09-19 Roozbeh Gharakhloo , Tomas Lasic Latimer

The number of triangles in a graph is useful to deduce a plethora of important features of the network that the graph is modeling. However, finding the exact value of this number is computationally expensive. Hence, a number of…

Data Structures and Algorithms · Computer Science 2017-10-30 Duru Türkoğlu , Ata Turk

In the setting of entangled single-sample distributions, the goal is to estimate some common parameter shared by a family of $n$ distributions, given one single sample from each distribution. This paper studies mean estimation for entangled…

Machine Learning · Computer Science 2020-07-14 Yingyu Liang , Hui Yuan

A powerful framework for studying graphs is to consider them as geometric graphs: nodes are randomly sampled from an underlying metric space, and any pair of nodes is connected if their distance is less than a specified neighborhood radius.…

Machine Learning · Computer Science 2022-11-28 Raffaele Paolino , Aleksandar Bojchevski , Stephan Günnemann , Gitta Kutyniok , Ron Levie

We consider random geometric graphs on the plane characterized by a non-uniform density of vertices. In particular, we introduce a graph model where $n$ vertices are independently distributed in the unit disc with positions, in polar…

Disordered Systems and Neural Networks · Physics 2022-04-06 C. T. Martinez-Martinez , J. A. Mendez-Bermudez , Francisco A. Rodrigues , Ernesto Estrada

Many applications in network analysis require algorithms to sample uniformly at random from the set of all graphs with a prescribed degree sequence. We present a Markov chain based approach which converges to the uniform distribution of all…

Discrete Mathematics · Computer Science 2010-03-05 Annabell Berger , Matthias Müller-Hannemann

We present a new framework for creating elegant algorithms for exact uniform sampling of important Catalan structures, such as triangulations of convex polygons, Dyck words, monotonic lattice paths and mountain ranges. Along with sampling,…

Discrete Mathematics · Computer Science 2018-03-13 Alexandros Angelopoulos , Eleni Bakali

Starting with a collection of $n$ oriented polygonal discs, with an even number $N$ of sides in total, we generate a random oriented surface by randomly matching the sides of discs and properly gluing them together. Encoding the surface in…

Combinatorics · Mathematics 2015-03-09 Sergei Chmutov , Boris Pittel

We investigate the asymptotic structure of a random perfect graph $P_n$ sampled uniformly from the perfect graphs on vertex set $\{1,\ldots,n\}$. Our approach is based on the result of Pr\"omel and Steger that almost all perfect graphs are…

Combinatorics · Mathematics 2017-09-07 Colin McDiarmid , Nikola Yolov

Graph sampling allows mining a small representative subgraph from a big graph. Sampling algorithms deploy different strategies to replicate the properties of a given graph in the sampled graph. In this study, we provide a comprehensive…

Social and Information Networks · Computer Science 2021-02-17 Muhammad Irfan Yousuf , Izza Anwer , Raheel Anwar

The article starts with some introductory material about resolution graphs of normal surface singularities (definitions, topological/homological properties, etc). We then discuss the case when the normal surface singularity is an N-fold…

Algebraic Geometry · Mathematics 2009-09-25 András Némethi

Approximate random $k$-colouring of a graph $G$ is a well studied problem in computer science and statistical physics. It amounts to constructing a $k$-colouring of $G$ which is distributed close to {\em Gibbs distribution} in polynomial…

Discrete Mathematics · Computer Science 2016-09-21 Charilaos Efthymiou

The recent extension of permutation entropy and its derivatives to graph signals has opened up new horizons for the analysis of complex, high-dimensional systems evolving on networks. However, these measures are all fundamentally rooted in…

Signal Processing · Electrical Eng. & Systems 2026-04-08 Mei-San Maggie Lei , John Stewart Fabila Carrasco , Javier Escudero

This work concerns sampling of smooth signals on arbitrary graphs. We first study a structured sampling strategy for such smooth graph signals that consists of a random selection of few pre-defined groups of nodes. The number of groups to…

Social and Information Networks · Computer Science 2017-05-08 Gilles Puy , Patrick Pérez

3D printing of surfaces has become an established method for prototyping and visualisation. However, surfaces often contain certain degenerations, such as self-intersecting faces or non-manifold parts, which pose problems in obtaining a 3D…

Computational Geometry · Computer Science 2024-05-28 Christian Amend , Tom Goertzen

Distribution testing can be described as follows: $q$ samples are being drawn from some unknown distribution $P$ over a known domain $[n]$. After the sampling process, a decision must be made about whether $P$ holds some property, or is far…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-12-04 Uri Meir

We describe some theoretical results on triangulations of surfaces and we develop a theory on roots, decompositions and genus-surfaces. We apply this theory to describe an algorithm to list all triangulations of closed surfaces with at most…

Combinatorics · Mathematics 2019-01-30 Gennaro Amendola

We classify homomorphisms from the braid group on $n$ strands to the pure mapping class group of a nonoriantable surface of genus $g$. For $n\ge 14$ and $g\le 2\lfloor{n/2}\rfloor+1$ every such homomorphism is either cyclic, or it maps…

Geometric Topology · Mathematics 2025-07-18 Michał Stukow , Błażej Szepietowski

Sampling methods (e.g., node-wise, layer-wise, or subgraph) has become an indispensable strategy to speed up training large-scale Graph Neural Networks (GNNs). However, existing sampling methods are mostly based on the graph structural…

Machine Learning · Computer Science 2021-09-07 Weilin Cong , Rana Forsati , Mahmut Kandemir , Mehrdad Mahdavi

We consider the triangle-free process: given an integer n, start by taking a uniformly random ordering of the edges of the complete n-vertex graph K_n. Then, traverse the ordered edges and add each traversed edge to an (initially empty)…

Combinatorics · Mathematics 2009-07-06 Guy Wolfovitz