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 year
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:
- A general-purpose Python package for Koopman theory using deep learning.☆110Updated last month
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆79Updated last year
- ☆89Updated 2 years ago
- Consistent Koopman Autoencoders☆74Updated 2 years ago
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆48Updated 4 years ago
- ☆45Updated 4 years ago
- AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)☆44Updated 3 years ago
- Koopman Reduced-Order Nonlinear Identification and Control☆91Updated 5 years ago
- A framework for neural network control of dynamical systems over graphs.☆56Updated 3 years ago
- Data-driven dynamical systems toolbox.☆77Updated last week
- Learning Koopman operator by EDMD with trainable dictionary☆26Updated 3 years ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆59Updated 3 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
- ☆34Updated 2 years ago
- Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.☆98Updated 3 years ago
- Koopman Mode Decomposition☆73Updated 8 years ago
- Learning dynamical systems from data: Koopman☆16Updated 5 years ago
- Here you can find the code for the paper "Training robust neural networks using Lipschitz bounds"☆10Updated 5 years ago
- Software to train neural networks via Koopman operator theory (see Dogra and Redman "Optimizing Neural Networks via Koopman Operator Theo…☆21Updated 2 years ago
- Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems☆30Updated 3 years ago
- PyTorch Implementation of Lusch et al DeepKoopman☆14Updated 2 years ago
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆42Updated 6 years ago
- Official code for AL-PINNS: Augmented Lagrangian relaxation method for Physics-Informed Neural Networks☆11Updated 2 years ago
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆31Updated last year
- Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".☆38Updated 3 years ago
- Compressive dynamic mode decomposition with control for compressive system identification☆40Updated 7 years ago
- Koopman operator identification library in Python, compatible with `scikit-learn`☆95Updated last month
- ☆10Updated 2 years ago
- ☆41Updated 7 years ago
- Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants. Proceedings of the Royal S…☆10Updated last year