Geometry Helps to Compare Persistence Diagrams

DOI10.1137/1.9781611974317.9zbMath1430.68376OpenAlexW2766197321MaRDI QIDQ5232550

Michael Kerber, Arnur Nigmetov, Dmitriy Morozov

Publication date: 12 September 2019

Published in: 2016 Proceedings of the Eighteenth Workshop on Algorithm Engineering and Experiments (ALENEX) (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/1.9781611974317.9

Mathematics Subject Classification ID

Persistent homology and applications, topological data analysis (55N31) Graph theory (including graph drawing) in computer science (68R10) Computer graphics; computational geometry (digital and algorithmic aspects) (68U05)

Related Items (6)

Nonparametric Estimation of Probability Density Functions of Random Persistence Diagrams ⋮ Geometry Helps to Compare Persistence Diagrams ⋮ \(A_\infty\) persistent homology estimates detailed topology from pointcloud datasets ⋮ Inferring symbolic dynamics of chaotic flows from persistence ⋮ Topological Machine Learning with Persistence Indicator Functions ⋮ Computing Minimal Presentations and Bigraded Betti Numbers of 2-Parameter Persistent Homology

This page was built for publication: Geometry Helps to Compare Persistence Diagrams