Enhancing predictive capabilities in data-driven dynamical modeling with automatic differentiation: Koopman and neural ODE approaches
C Ricardo Constante-Amores, AJ Linot… - … Journal of Nonlinear …, 2024 - pubs.aip.org
Data-driven approximations of the Koopman operator are promising for predicting the time
evolution of systems characterized by complex dynamics. Among these methods, the …
evolution of systems characterized by complex dynamics. Among these methods, the …
Invariance proximity: Closed-form error bounds for finite-dimensional Koopman-based models
A popular way to approximate the Koopman operator's action on a finite-dimensional
subspace of functions is via orthogonal projections. The quality of the projected model …
subspace of functions is via orthogonal projections. The quality of the projected model …
[PDF][PDF] Efficient Computation of Invariance Proximity: Closed-Form Error Bounds for Finite-Dimensional Koopman-Based Models
M Haselia, J Cortésa - terrano.ucsd.edu
A popular way to approximate the Koopman operator's action on a finite-dimensional
subspace of functions is via orthogonal projections. The quality of the projected model …
subspace of functions is via orthogonal projections. The quality of the projected model …