Data-driven modeling and forecasting of chaotic dynamics on inertial manifolds constructed as spectral submanifolds
From MaRDI portal
Publication:6552138
DOI10.1063/5.0179741zbMATH Open1545.37071MaRDI QIDQ6552138
György Haller, Aihui Liu, Joar Axås
Publication date: 8 June 2024
Published in: Chaos (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Discovering governing equations from data by sparse identification of nonlinear dynamical systems
- Inertial manifolds
- Prediction of multivariate chaotic time series with local polynomial fitting
- Determining Lyapunov exponents from a time series
- Inertial manifolds for nonlinear evolutionary equations
- Nonlinear prediction of chaotic time series
- Embedology
- Statistics, probability and chaos. With discussion and a rejoinder by the author
- Nonlinear dynamics in economics. A theoretical and statistical approach to agriculture markets
- Poincaré maps for multiscale physics discovery and nonlinear Floquet theory
- Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders
- A practical method for calculating largest Lyapunov exponents from small data sets
- An equation for continuous chaos
- Nonlinear normal modes and spectral submanifolds: existence, uniqueness and use in model reduction
- Independent coordinates for strange attractors from mutual information
- An investigation of chaotic Kolmogorov flows
- Chaos, Scattering and Statistical Mechanics
- A nine-dimensional Lorenz system to study high-dimensional chaos
- Ergodic theory of chaos and strange attractors
- Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks
- Deterministic Nonperiodic Flow
- Dynamic Mode Decomposition and Its Variants
- Invariant recurrent solutions embedded in a turbulent two-dimensional Kolmogorov flow
- Chaotic Dynamics
- On the State Space Geometry of the Kuramoto–Sivashinsky Flow in a Periodic Domain
- Differentiable manifolds.
- Methods of continuation and their implementation in the COCO software platform with application to delay differential equations
- Nonlinear Model Reduction to Fractional and Mixed-Mode Spectral Submanifolds
- Data-driven reduced-order modeling of spatiotemporal chaos with neural ordinary differential equations
This page was built for publication: Data-driven modeling and forecasting of chaotic dynamics on inertial manifolds constructed as spectral submanifolds