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High order networks are weighted hypergraphs col- lecting relationships between elements of tuples, not necessarily pairs. Valid metric distances between high order networks have been defined but they are difficult to compute when the…

社会与信息网络 · 计算机科学 2016-05-04 Weiyu Huang , Alejandro Ribeiro

Thresholding--the pruning of nodes or edges based on their properties or weights--is an essential preprocessing tool for extracting interpretable structure from complex network data, yet existing methods face several key limitations.…

社会与信息网络 · 计算机科学 2025-10-07 Adam Schroeder , Russell Funk , Jingyi Guan , Taylor Okonek , Lori Ziegelmeier

Hypergraph is a topological model for networks. In order to study the topology of hypergraphs, the homology of the associated simplicial complexes and the embedded homology have been invented. In this paper, we give some algorithms to…

代数拓扑 · 数学 2018-01-03 Shiquan Ren , Chengyuan Wu , Stephane Bressan , Jie Wu

Long lived topological features are distinguished from short lived ones (considered as topological noise) in simplicial complexes constructed from complex networks. A new topological invariant, persistent homology, is determined and…

数学物理 · 物理学 2009-11-13 Danijela Horak , Slobodan Maletic , Milan Rajkovic

A standard problem in applied topology is how to discover topological invariants of data from a noisy point cloud that approximates it. We consider the case where a sample is drawn from a properly embedded C1-submanifold without boundary in…

一般拓扑 · 数学 2026-03-03 Sara Kalisnik , Davorin Lesnik

As complex networks find applications in a growing range of disciplines, the diversity of naturally occurring and model networks being studied is exploding. The adoption of a well-developed collection of network taxonomies is a natural…

组合数学 · 数学 2016-01-25 Ann Sizemore , Chad Giusti , Danielle Bassett

In real-world systems, the relationships and connections between components are highly complex. Real systems are often described as networks, where nodes represent objects in the system and edges represent relationships or connections…

代数拓扑 · 数学 2024-06-24 Shen Zhang

The application of network techniques to the analysis of neural data has greatly improved our ability to quantify and describe these rich interacting systems. Among many important contributions, networks have proven useful in identifying…

定量方法 · 定量生物学 2018-06-14 Ann E. Sizemore , Jennifer Phillips-Cremins , Robert Ghrist , Danielle S. Bassett

The statistical mechanical approach to complex networks is the dominant paradigm in describing natural and societal complex systems. The study of network properties, and their implications on dynamical processes, mostly focus on locally…

统计力学 · 物理学 2013-06-27 Giovanni Petri , Martina Scolamiero , Irene Donato , Francesco Vaccarino

Inference of topological and geometric attributes of a hidden manifold from its point data is a fundamental problem arising in many scientific studies and engineering applications. In this paper we present an algorithm to compute a set of…

计算几何 · 计算机科学 2009-12-02 Tamal K. Dey , Jian Sun , Yusu Wang

Biological and physical systems often exhibit distinct structures at different spatial/temporal scales. Persistent homology is an algebraic tool that provides a mathematical framework for analyzing the multi-scale structures frequently…

代数拓扑 · 数学 2016-02-01 Jonathan Jaquette , Miroslav Kramár

This article proposes an algorithm that constructs a Sullivan minimal model for any simply connected simplicial set with effective homology and thereby allows one to decide algorithmically whether two simply connected spaces represented by…

代数拓扑 · 数学 2025-12-25 Mária Šimková

Persistent homology is a mathematical tool used for studying the shape of data by extracting its topological features. It has gained popularity in network science due to its applicability in various network mining problems, including…

代数拓扑 · 数学 2023-06-21 Mehmet Emin Aktas , Thu Nguyen , Rakin Riza , Muhammad Ifte Islam , Esra Akbas

Computation of persistent homology of simplicial representations such as the Rips and the C\v{e}ch complexes do not efficiently scale to large point clouds. It is, therefore, meaningful to devise approximate representations and evaluate the…

计算几何 · 计算机科学 2020-09-29 Naheed Anjum Arafat , Debabrota Basu , Stéphane Bressan

Complex networks with high numbers of nodes or links are often difficult to analyse. However, not all elements contribute equally to their structural patterns. A small number of elements (the hubs) seem to play a particularly relevant role…

物理与社会 · 物理学 2007-09-24 Bernat Corominas-Murtra , Sergi Valverde , Carlos Rodríguez-Caso , Ricard V. Solé

Among all characteristics exhibited by natural and man-made networks the small-world phenomenon is surely the most relevant and popular. But despite its significance, a reliable and comparable quantification of the question `how small is a…

物理与社会 · 物理学 2019-11-27 Gorka Zamora-López , Romain Brasselet

Topological landscape is introduced for networks with functions defined on the nodes. By extending the notion of gradient flows to the network setting, critical nodes of different indices are defined. This leads to a concise and…

统计方法学 · 统计学 2012-05-01 E. Weinan , Jianfeng Lu , Yuan Yao

We study the problems of finding a minimum cycle basis (a minimum weight set of cycles that form a basis for the cycle space) and a minimum homology basis (a minimum weight set of cycles that generates the $1$-dimensional…

数据结构与算法 · 计算机科学 2016-07-19 Glencora Borradaile , Erin Wolf Chambers , Kyle Fox , Amir Nayyeri

We define an algebraic setup of homology for hypergraphs, which defaults to simplicial homology in the case of graphs, and study its basic properties. As part of our study we define algebraic spanning trees of hypergraphs, along with…

组合数学 · 数学 2021-09-07 Reinhard Diestel

The purpose of this paper is to introduce a version of singular homology based on smooth mappings of manifolds with corners. Although variants of such a theory exists in the literature, we felt that certain points were not adequately…

代数拓扑 · 数学 2014-09-04 Max Lipyanskiy
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