Talk - Topological Data Analysis Based Models of Evolving Higher-Order Networks
Abstract
The field of complex networks capturing pairwise interactions has seen significant advancements over the past decades. On the other hand, higher-order networks capable of describing more complex group interactions, have only recently gained substantial attention. To study these networks, sophisticated mathematical tools, such as stochastic simplicial complex models and topological data analysis (TDA), are required. Despite former research, higher-order network models and their connection with real-world datasets remain poorly understood. The goal of this research project is to develop stochastic simplicial models to describe the structure and dynamics of higher-order networks, with applications in understanding scientific collaborations and social networks.
