Exploring persistent local homology in topological data analysis

Brittany Terese Fasy; Bei Wang

ICASSP 2016accepted0 citations

Exploring persistent local homology in topological data analysis

Abstract

Topological data analysis (TDA) has rapidly grown in popularity in recent years. One of the emerging tools is persistent local homology, which can be used to extract local structure from a dataset. In this paper, we provide a survey that explores this new tool, emphasizing its use in data analysis.

BibTeX

@inproceedings{icassp2016_exploringpersist,
  title = {Exploring persistent local homology in topological data analysis},
  author = {Brittany Terese Fasy and Bei Wang},
  booktitle = {ICASSP 2016},
  year = {2016}
}