Understanding High-dimensional Stochastic Dynamics on Realistic Networks

Explore a conference talk from the Big Data Conference 2024 where Brown University's Kavita Ramanan delves into analyzing high-dimensional stochastic dynamics on realistic networks. Learn about innovative approaches to understanding complex systems involving randomly evolving particles that interact across networks, applicable to diverse phenomena from disease spread to neural networks and computer load balancing. Discover a novel methodology that overcomes dimensionality challenges in analyzing sparse and random networks, moving beyond traditional dense-network mean-field approximations. Examine practical applications through epidemiological model case studies, drawing from collaborative research with Michel Davydov, Ankan Ganguly, and Juniper Cocomello.