haller-group / DataDrivenLinearizationLinks
Constructing linearizing transformations for reduced-order modeling of nonlinear dynamical systems
☆11Updated last year
Alternatives and similar repositories for DataDrivenLinearization
Users that are interested in DataDrivenLinearization are comparing it to the libraries listed below
Sorting:
- ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis☆55Updated 2 years ago
- This repository contains code, which was used to generate large-scale results in the HINTS paper.☆31Updated last year
- ☆16Updated last year
- Data-driven reduced order modeling for nonlinear dynamical systems☆90Updated 4 months ago
- Deep learning framework for model reduction of dynamical systems☆21Updated 4 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated last month
- ☆32Updated 3 years ago
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆33Updated 3 years ago
- The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-…☆19Updated 3 years ago
- Code repository for "Learned Turbulence Modelling with Differentiable Fluid Solvers"☆39Updated 3 years ago
- Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)☆59Updated 4 years ago
- ☆15Updated 5 years ago
- A differentiable finite element analysis solver for structural optimization based on JAX☆33Updated 3 months ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- Dimensionless learning codes for our paper called "Data-driven discovery of dimensionless numbers and governing laws from scarce measurem…☆39Updated last month
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆50Updated 2 years ago
- ☆57Updated last year
- Code for the paper "Structure-preserving neural networks" published in Journal of Computational Physics (JCP).☆19Updated 2 years ago
- Computation of invariant manifolds in high-dimensional mechanics problems☆26Updated last year
- Enhancing Dynamic Mode Decomposition using Autoencoder Networks.☆33Updated 4 years ago
- Example problems in Physics informed neural network in JAX☆81Updated 2 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- ☆16Updated last year
- Sparse Identification of Nonlinear Dynamics for Boundary Value Problems☆13Updated 4 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆69Updated 5 years ago
- 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 paper "Learning the Solution Operator of Boundary Value Problems using Graph Neural Networks"☆20Updated last year
- Pseudospectral Kolmogorov Flow Solver☆41Updated last year
- Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.☆15Updated 2 years ago
- ☆20Updated last month