Machine-Learning-Dynamical-Systems / kooplearn
A Python package to learn the Koopman operator.
☆56Updated 5 months ago
Alternatives and similar repositories for kooplearn:
Users that are interested in kooplearn are comparing it to the libraries listed below
- ☆29Updated 2 years ago
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆26Updated last year
- Data-driven dynamical systems toolbox.☆74Updated this week
- Nonparametric Differential Equation Modeling☆53Updated last year
- Consistent Koopman Autoencoders☆74Updated last year
- ☆10Updated 6 months ago
- A general-purpose Python package for Koopman theory using deep learning.☆100Updated 2 months ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆54Updated 2 years ago
- Koopman operator identification library in Python, compatible with `scikit-learn`☆74Updated 5 months ago
- Implementation of the work Variational multiple shooting for Bayesian ODEs with Gaussian processes☆12Updated 2 years ago
- A framework for neural network control of dynamical systems over graphs.☆58Updated 2 years ago
- Python model for constrained GP☆24Updated 4 years ago
- Codes for Linear and Nonlinear Disambiguation Optimization (LANDO)☆29Updated 3 years ago
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆48Updated 3 years ago
- A Python package for linear subspace identification, nonlinear system identification, and nonlinear regression using Jax☆32Updated last month
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆73Updated 11 months ago
- Symbolic Identification of Non-linear Dynamics. The method generalizes the SINDy algorithm by combining sparse and genetic-programming-ba…☆74Updated 2 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- Code and files related to random side projects☆21Updated 3 years ago
- ☆87Updated 2 years ago
- ☆15Updated 4 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
- Construction of control systems from predictive models via Quantization, Simulation, Modeling, Optimization☆11Updated last year
- ☆27Updated 2 months ago
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆45Updated 4 years ago
- Learning unknown ODE models with Gaussian processes☆26Updated 6 years ago
- Discovers high dimensional models from 1D data using deep delay autoencoders☆34Updated 2 years ago
- Exploring how to to deal with uncertain inputs with gaussian process regression models.☆27Updated 4 years ago
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆25Updated last year
- ☆12Updated 2 years ago