Date: 05 May 2021 | Speaker: Alvaro Torras Casas
Briefly, I will explain what is topology and why it is being used in neuroscience, crystallography, molecular biology and more. Then I will introduce some python libraries that are ready for analyzing different kinds of datasets, ranging from signals to images and low dimensional point clouds. We will briefly review the whole TDA pipeline: starting from raw data, going through topological summaries and outcome interpretation. Ahead of the talk, I will be sending a jupyter notebook with examples using the library scikit-tda.py. If time permits I will go over spectral sequences and their use in distributing persistent homology computations. In particular, I will present some examples using permaviss.py which computes topological summaries through the use of the Mayer-Vietoris spectral sequence.
