96 citations · 285 across the 13 of their papers we have counts for
6 papers · 1 filter
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…
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…
Data-driven control of spatiotemporal chaos with reduced-order neural ODE-based models and reinforcement learning
Kevin Zeng, Alec J. Linot, Michael D. Graham
Deep reinforcement learning (RL) is a data-driven method capable of discovering complex control strategies for high-dimensional systems, making it promising for flow control applic…
Stabilized Neural Ordinary Differential Equations for Long-Time Forecasting of Dynamical Systems
Alec J. Linot, Joshua W. Burby, Qi Tang +3
In data-driven modeling of spatiotemporal phenomena careful consideration often needs to be made in capturing the dynamics of the high wavenumbers. This problem becomes especially…
Data-Driven Reduced-Order Modeling of Spatiotemporal Chaos with Neural Ordinary Differential Equations
Alec J. Linot, Michael D. Graham
Dissipative partial differential equations that exhibit chaotic dynamics tend to evolve to attractors that exist on finite-dimensional manifolds. We present a data-driven reduced o…
Deep learning to discover and predict dynamics on an inertial manifold
Alec J. Linot, Michael D. Graham
A data-driven framework is developed to represent chaotic dynamics on an inertial manifold (IM), and applied to solutions of the Kuramoto-Sivashinsky equation. A hybrid method comb…