haller-group / DataDrivenLinearization
Constructing linearizing transformations for reduced-order modeling of nonlinear dynamical systems
☆10Updated 9 months ago
Alternatives and similar repositories for DataDrivenLinearization
Users that are interested in DataDrivenLinearization are comparing it to the libraries listed below
Sorting:
- ☆16Updated 9 months ago
- Deep learning framework for model reduction of dynamical systems☆21Updated 4 years ago
- Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.☆15Updated last year
- ☆10Updated last year
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆30Updated last year
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆30Updated 2 years ago
- Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms☆11Updated 6 months ago
- ☆34Updated 3 weeks ago
- Multi-fidelity reduced-order surrogate modeling☆22Updated 2 weeks ago
- ☆14Updated 9 months ago
- The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-…☆19Updated 2 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆28Updated last year
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated last month
- Sparse Identification of Nonlinear Dynamics for Boundary Value Problems☆12Updated 4 years ago
- Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems☆29Updated 2 years ago
- Multifidelity DeepONet☆33Updated last year
- This codes calculates the dimensionalized POD and uses SINDy from the PySINDy python package to build a data-driven model for it. The cod…☆19Updated 4 years ago
- A novel DeepONet architecture that is specifically designed for generating predictions on different 3D geometries discretized by differen…☆14Updated 9 months ago
- Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)☆56Updated 4 years ago
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆24Updated last year
- Code for the paper "Structure-preserving neural networks" published in Journal of Computational Physics (JCP).☆19Updated last year
- Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning☆17Updated last year
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆25Updated 3 years ago
- Code for "Robust flow field reconstruction from limited measurements vis sparse representation" (J. Callaham, K. Maeda, and S. Brunton 20…☆14Updated 6 years ago
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆14Updated last year
- ☆13Updated 3 years ago
- Enhancing Dynamic Mode Decomposition using Autoencoder Networks.☆30Updated 4 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆68Updated 4 years ago
- A library of tools for computing variants of Dynamic Mode Decomposition☆47Updated 7 years ago