yriyazi / Koopman-Operator-and-Deep-Neural-Networks-ISAV2023Links
In this work, we present a novel approach that combines the power of Koopman operators and deep neural networks to generate a linear representation of the Duffing oscillator. This approach enables effective parameter estimation and accurate prediction of the oscillator's future behavior.
☆10Updated last week
Alternatives and similar repositories for Koopman-Operator-and-Deep-Neural-Networks-ISAV2023
Users that are interested in Koopman-Operator-and-Deep-Neural-Networks-ISAV2023 are comparing it to the libraries listed below
Sorting:
- AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)☆44Updated 3 years ago
- ☆89Updated 2 years ago
- ☆13Updated last year
- A general-purpose Python package for Koopman theory using deep learning.☆116Updated 2 months ago
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆81Updated last year
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆50Updated 5 years ago
- Consistent Koopman Autoencoders☆75Updated 2 years ago
- A framework for neural network control of dynamical systems over graphs.☆56Updated 3 years ago
- Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems☆30Updated 3 years ago
- Learning Koopman operator by EDMD with trainable dictionary☆27Updated 3 years ago
- ☆45Updated 4 years ago
- Koopman Reduced-Order Nonlinear Identification and Control☆92Updated 5 years ago
- Material for the tutorial on "Physics-Informed Machine Learning (PIML) for Modeling and Control of Dynamical Systems" presented at the Am…☆19Updated last year
- Data-driven dynamical systems toolbox.☆78Updated last month
- Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants. Proceedings of the Royal S…☆11Updated last year
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆59Updated 3 years ago
- ☆42Updated 7 years ago
- AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control☆33Updated 3 years ago
- A Python package to learn the Koopman operator.☆63Updated last week
- Deep learning assisted dynamic mode decomposition☆19Updated 4 years ago
- Code for Learning Sparse Nonlinear Dynamics via Mixed Integer Optimization☆16Updated 3 years ago
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆31Updated 2 years ago
- Empowering extended Kalman filter (EKF) with Sparse Identification of Nonlinear Dynamics (SINDy)☆67Updated 7 months ago
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆53Updated 4 years ago
- Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".☆38Updated 3 years ago
- SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics☆156Updated 4 years ago
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆43Updated 6 years ago
- ☆10Updated 2 years ago
- Koopman Mode Decomposition☆74Updated 8 years ago
- ☆20Updated 5 years ago