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# Ashleigh Thomas : Practical multiparameter persistent homology

In this talk we will explore a mathematical data analysis tool called persistent homology and look specifically into how we can turn topological information into useful data for statistical techniques. The problem is one of translation: persistent homology outputs a module, but statistics is formulated for objects in metric, vector, Banach, and Hilbert spaces. We'll see some of the ways this issue can be dealt with in a special case (single-parameter persistence) and discuss which of those techniques are viable for a more general case (multiparameter persistence).

**Category**: Graduate/Faculty Seminar**Duration**: 01:14:42**Date**: April 9, 2018 at 11:55 AM**Views**: 196-
**Tags:**seminar, Graduate/faculty Seminar

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