Persistent Homology Talk at UIC: Slides by Jeremy Kun.
From the post:
Today I gave a twenty-minute talk at UI Chicago as part of the first annual Chicago Area Student SIAM Conference. My talk was titled “Recent Developments in Persistent Homology,” and it foreshadows the theoretical foundations and computational implementations we’ll be laying out on this blog in the coming months. Here’s the abstract:
Persistent homology is a recently developed technique for analyzing the topology of data sets. We will give a rough overview of the technique and sample successful applications to areas such as natural image analysis & texture classification, breast and liver cancer classification, molecular dynamical systems, and others.
The talk was received very well — mostly, I believe, because I waved my hands on the theoretical aspects and spent most of my time talking about the applications.
The slides.
Jeremy doesn’t hold out much hope the slides will be useful sans the lecture surrounding them.
He does includes references so see what you think of the slides + references.