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Feature Extraction Using Topological Data Analysis for Machine Learning and Network Science Applications
Many real-world data sets can be viewed as a noisy sampling of an unknown high-dimensional topological space. The emergence and development of topological data analysis (TDA) over the last fifteen years or so provides a suite of tools to understand and exploit the topological structure of the underlying space from a multi-scale ...