{"title":"Geometric sampling of networks","authors":"Vladislav Barkanass;Jürgen Jost;Emil Saucan;Edwin Hancock","doi":"10.1093/comnet/cnac014","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"100","ListUrlMain":"https://ieeexplore.ieee.org/document/10070448/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
网络的几何抽样
受基于Ricci曲率的流形采样方法和结果的启发,我们提出了一种类似的网络方法。为此,我们呼吁使用三种类型的离散曲率,即图Forman-、全Forman-和Haantjes–Ricci曲率进行基于边缘和基于节点的采样。研究了原始流形的Ricci曲率和Ricci曲率驱动的离散化的Ricci弯曲之间的关系,我们证明了所得网络的Forman–Ricci曲率与给定光滑流形的Riccci曲率之间存在强联系。我们还介绍了在真实网络上的实验结果,以及在图像处理中出现的方形网格的实验结果。此外,我们考虑拟合Ricci流,并将其用于检测网络的主干。
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