Topological Machine Learning with Persistence Indicator Functions

DOI10.1007/978-3-030-43036-8_6zbMath1465.68230arXiv1907.13496OpenAlexW2965224253MaRDI QIDQ5147730

F. Sadlo, Bastian Rieck, Heike Leitte

Publication date: 28 January 2021

Published in: Mathematics and Visualization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1907.13496

Mathematics Subject Classification ID

Persistent homology and applications, topological data analysis (55N31) Learning and adaptive systems in artificial intelligence (68T05)

Related Items

Persistence curves: a canonical framework for summarizing persistence diagrams

Uses Software

• Scikit
• bootstrap
• graphkernels
• PersistenceImages

Cites Work

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• Fréchet means for distributions of persistence diagrams
• Extreme elevation on a 2-manifold
• Stability of persistence diagrams
• Lipschitz functions have \(L_{p}\)-stable persistence
• Topology of random geometric complexes: a survey
• Topological persistence and simplification
• Introduction to empirical processes and semiparametric inference
• Geometry Helps to Compare Persistence Diagrams
• Persistence Images: A Stable Vector Representation of Persistent Homology
• Algorithms – ESA 2004
• Statistical topological data analysis using persistence landscapes