Identifying Nonlinear Dynamics with High Confidence from Sparse Data

Identifying Nonlinear Dynamics with High Confidence from Sparse Data

Explore cutting-edge research on identifying nonlinear dynamics from sparse data in this 29-minute conference talk by Bogdan Batko from Jagiellonian University. Delivered as part of the Fourth Symposium on Machine Learning and Dynamical Systems at the Fields Institute, gain insights into innovative approaches for analyzing complex systems with limited information. Discover techniques for achieving high confidence in dynamical system identification despite data scarcity, and learn how these methods can be applied across various scientific disciplines.