most citedData-driven state-space and Koopman operator models of coherent state dynamics on invariant manifolds

19 citations · 35 across the 9 of their papers we have counts for

collaborators
Showing cs.LGShow all

2 papers · 1 filter

cs.LG2023★ 1 cited

Building symmetries into data-driven manifold dynamics models for complex flows: application to two-dimensional Kolmogorov flow

Carlos E. Pérez De Jesús, Alec J. Linot, Michael D. Graham

Data-driven reduced-order models of the dynamics of complex flows are important for tasks related to design, understanding, prediction, and control. Many flows obey symmetries, and…

cs.LG2023

Enhancing Predictive Capabilities in Data-Driven Dynamical Modeling with Automatic Differentiation: Koopman and Neural ODE Approaches

C. Ricardo Constante-Amores, Alec J. Linot, Michael D. Graham

Data-driven approximations of the Koopman operator are promising for predicting the time evolution of systems characterized by complex dynamics. Among these methods, the approach k…