A new non-Archimedean metric on persistent homology
DOI10.1007/s00180-021-01187-zzbMath1505.62172arXiv2012.02655OpenAlexW4206818381MaRDI QIDQ2095728
Publication date: 15 November 2022
Published in: Computational Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2012.02655
hierarchical clusteringmachine learningtopological data analysispersistent homologycophenetic distance
Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Persistent homology and applications, topological data analysis (55N31) Learning and adaptive systems in artificial intelligence (68T05) Other homology theories in algebraic topology (55N35) Topological data analysis (62R40)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Stability of persistence diagrams
- Comparing trees via crossing minimization
- Statistical theory in clustering
- Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
- An extension of the \(K\)-means algorithm to clustering skewed data
- Computing persistent homology
- Topological persistence and simplification
- Hierarchical clustering schemes
- Non-parametric clustering over user features and latent behavioral functions with dual-view mixture models
- Drawing (complete) binary tanglegrams
- Persistence curves: a canonical framework for summarizing persistence diagrams
- Persistence Terrace for Topological Inference of Point Cloud Data
- Statement forNaval Research Logistics
- 10.1162/153244303321897735
- Persistent homology and applied homotopy theory
- Handbook of Homotopy Theory
- Persistence Images: A Stable Vector Representation of Persistent Homology
- PERSISTENCE BARCODES FOR SHAPES
- Statistical topological data analysis using persistence landscapes
- Barcodes: The persistent topology of data
