4 papers
Efficient pseudometrics for data-driven comparisons of nonlinear dynamical systems
Bryan Glaz
Computationally efficient solutions for pseudometrics quantifying deviation from topological conjugacy between dynamical systems are presented. Deviation from conjugacy is quantifi…
Unsupervised learning for anticipating critical transitions
Shirin Panahi, Ling-Wei Kong, Bryan Glaz +2
For anticipating critical transitions in complex dynamical systems, the recent approach of parameter-driven reservoir computing requires explicit knowledge of the bifurcation param…
Machine-learning prediction of tipping with applications to the Atlantic Meridional Overturning Circulation
Shirin Panahi, Ling-Wei Kong, Mohammadamin Moradi +4
Anticipating a tipping point, a transition from one stable steady state to another, is a problem of broad relevance due to the ubiquity of the phenomenon in diverse fields. The ste…
Learning to learn ecosystems from limited data -- a meta-learning approach
Zheng-Meng Zhai, Bryan Glaz, Mulugeta Haile +1
A fundamental challenge in developing data-driven approaches to ecological systems for tasks such as state estimation and prediction is the paucity of the observational or measurem…