Interacting System

Interacting systems research focuses on understanding and modeling the dynamics of systems composed of multiple interacting components, aiming to predict their collective behavior. Current research emphasizes developing efficient algorithms and model architectures, such as graph neural networks, stochastic differential equations, and variational methods, to learn these dynamics from data, often addressing challenges posed by high dimensionality, stochasticity, and sparse observations. These advancements have significant implications for diverse fields, including physics, biology, and engineering, enabling improved forecasting, control, and anomaly detection in complex systems.