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Comparing Graphs via Persistence Distortion
[article]
2017
arXiv
pre-print
Metric graphs are ubiquitous in science and engineering. For example, many data are drawn from hidden spaces that are graph-like, such as the cosmic web. A metric graph offers one of the simplest yet still meaningful ways to represent the non-linear structure hidden behind the data. In this paper, we propose a new distance between two finite metric graphs, called the persistence-distortion distance, which draws upon a topological idea. This topological perspective along with the metric space
arXiv:1503.07414v4
fatcat:5fzvzkot3ndnjkklgmzeiw2fpi