Institute-Eng-and-Comp-Mechanics-UStgt / ApHINLinks
A data-driven framework for the identification of latent port-Hamiltonian systems
☆18Updated this week
Alternatives and similar repositories for ApHIN
Users that are interested in ApHIN are comparing it to the libraries listed below
Sorting:
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆33Updated 3 years ago
- Companion code for Data-Driven Resolvent Analysis☆22Updated 4 years ago
- Code for ResDMD: data-driven spectral properties of Koopman Operators☆40Updated last year
- Transformed Generative Pre-Trained Physics-Informed Neural Networks (TGPT-PINN), a framework that extends Physics-Informed Neural Network…☆17Updated last year
- Dimensionless learning codes for our paper called "Data-driven discovery of dimensionless numbers and governing laws from scarce measurem…☆40Updated last month
- Solve mass spring damper system with phyics-informed neural networks in MATLAB☆13Updated last year
- ☆14Updated 3 years ago
- A Self-Training Physics-Informed Neural Network for Partial Differential Equations☆22Updated 2 years ago
- ☆20Updated 2 months ago
- Python tools for non-intrusive reduced order modeling☆20Updated 7 months ago
- Sparse Identification of Nonlinear Dynamics for Boundary Value Problems☆13Updated 4 years ago
- 🌌 Applications of Physics-Informed ML: A collection of notebooks from my Masters research, exploring how machine learning can solve scie…☆11Updated last year
- Code for "Robust flow field reconstruction from limited measurements vis sparse representation" (J. Callaham, K. Maeda, and S. Brunton 20…☆14Updated 7 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆26Updated 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 2 years ago
- Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems☆30Updated 3 years ago
- combination of sparse identification of nonlinear dynamics with Akaike information criteria☆16Updated 8 years ago
- Competitive Physics Informed Networks☆31Updated last year
- ☆12Updated 2 years ago
- SINDy-SA framework: enhancing nonlinear system identification with sensitivity analysis☆12Updated 6 months ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated last month
- Gaussian process-based interpretable latent space dynamics identification through deep autoencoder☆35Updated this week
- Neural Galerkin☆16Updated 2 years ago
- ☆16Updated last year
- Constructing linearizing transformations for reduced-order modeling of nonlinear dynamical systems☆11Updated last year
- Implementation of physics-informed PointNet (PIPN) for weakly-supervised learning of incompressible flows and thermal fields on irregular…☆11Updated 4 months ago
- ☆12Updated last week
- Interpretable machine learning (symbolic regression) using Genetic programming/Gene expression programming and Sparse regression used …☆34Updated 4 years ago
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆22Updated last year
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago