The mapper construction is a powerful tool from topological data analysis that is designed for the analysis and visualization of multivariate data. In this paper, we investigate a method for stitching a pair of univariate mappers together into a bivariate mapper, and study topological notions of information gains, referred to as topological gains, during such a process. We further provide implementations that visualize such topological gains for mapper graphs.
@article{arxiv.2105.01961,
title = {Stitch Fix for Mapper and Topological Gains},
author = {Youjia Zhou and Nathaniel Saul and Ilkin Safarli and Bala Krishnamoorthy and Bei Wang},
journal= {arXiv preprint arXiv:2105.01961},
year = {2021}
}