Graph Reconstruction via Discrete Morse Theory
Explore graph reconstruction techniques using discrete Morse theory in this insightful lecture. Delve into the fundamental problem of reconstructing hidden graphs from various types of potentially noisy input data. Learn about a specific framework for reconstructing hidden geometric graphs from density data using a persistence-guided discrete Morse-based approach. Examine the application of this framework in automatic road network reconstruction. Gain theoretical understanding of the framework, including guarantees of reconstruction when input data satisfies certain noise models. Discover the importance of graphs in various scientific and engineering applications, from geometric road networks in GIS to abstract protein-protein interaction networks. This talk, presented by Yusu Wang, covers joint work with collaborators Tamal K. Dey, Yanjie Li, Jiayuan Wang, and Suyi Wang.