TDA for Chromatic Point Clouds

Explore the application of Topological Data Analysis (TDA) to chromatic point clouds in this informative lecture. Learn how to extend the standard persistent homology pipeline to accommodate data points with additional type information, such as color. Discover techniques for detecting complex spatial relationships, like orange points surrounded by blue points, which have practical applications in spatial biology and medicine for understanding cell interactions. Delve into the innovative approach that combines kernel, image, and cokernel persistence with the chromatic alpha complex. Gain insights into interpreting the resulting "six-pack" of persistence diagrams and their features. Conclude with a hands-on demonstration of the Python implementation, encouraging audience participation in chromatic TDA experimentation. Access the accompanying GitHub repository for further exploration and practical application of the concepts presented.