February 27, 2024
Title: Distinguishing signal from noise in topological data analysis (MI talk)
Speaker: Felix Wierstra
Topological data analysis (TDA), and in particular, persistent homology, is a method used to extract higher geometric information from complex datasets and has proven highly successful in various scientific domains. In this talk, I will provide an introduction to TDA and explain its applications in studying fMRI scans and brain data, and stock prices. I will then discuss the statistical challenges that arise in interpreting the results of TDA and explain how this might be related to fractals. This is joint work with Roel Gisolf and Fernando A. N. Santos.