Overview

We are studying Topological Data Analysis with a focus on methods (approximate, parallel and distributed) to compute Persistent Homology (PH) on large and high-dimensional data sets. Our current studies focus on (i) partitioning coupled with parallel and distributed computing to expand the computation of PH for big data in moderate dimensions (<4); (ii) approximate methods to compute PH on higher dimensional data sets; and (iii) the computation of PH on streaming data.

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