This workshop brings together experts, researchers, and students to share research results in the cross-disciplinary area of machine learning and advanced dynamical system theory, and suggests important challenges that have yet to be addressed.
Advanced research in machine learning has provided an invaluable approach to analysing and forecasting complex systems based on observed data. Such data-driven technology has become increasingly indispensable for studies of dynamical systems where an analytical model is lacking, but observed data is available. This workshop will facilitate the cross-fertilisation between experts and researchers in machine learning and mathematics. There will be both pedagogical talks and recent research contributions that cover several areas of applications ranging from fluid dynamics to social network data.
