matlab-deep-learning / SciML-and-Physics-Informed-Machine-Learning-ExamplesLinks
This repository collates a number of MATLAB examples demonstrating Scientific Machine Learning (SciML) and Physics Informed Machine Learning.
☆120Updated this week
Alternatives and similar repositories for SciML-and-Physics-Informed-Machine-Learning-Examples
Users that are interested in SciML-and-Physics-Informed-Machine-Learning-Examples are comparing it to the libraries listed below
Sorting:
- MATLAB codes for physics-informed dynamic mode decomposition (piDMD)☆157Updated last year
- ☆25Updated last month
- This curriculum module introduces foundational concepts for solving the Navier-Stokes equations, including methods for interface advectio…☆139Updated 4 months ago
- A Computational Fluid Dynamics (CFD) course with Python☆94Updated last year
- Gaussian process-based interpretable latent space dynamics identification through deep autoencoder☆34Updated last week
- Python for Scientific Computing (FEniCS, PyTorch, VTK)☆123Updated last year
- Deep Learning for Reduced Order Modelling☆100Updated 3 years ago
- ☆83Updated last year
- MODULO (MODal mULtiscale pOd) is a software developed at the von Karman Institute to perform Multiscale Modal Analysis of numerical and e…☆92Updated last month
- Data-driven reduced order modeling for nonlinear dynamical systems☆85Updated 2 months ago
- Easy Reduced Basis method☆86Updated last month
- A Physics-Informed Neural Network to solve 2D steady-state heat equations.☆154Updated this week
- Basic implementation of physics-informed neural networks for solving differential equations☆92Updated 8 months ago
- This repository provides MATLAB code for the lid-driven cavity flow where incompressible Navier Stokes equation is numerically solved usi…☆113Updated last year
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆75Updated 3 years ago
- Multi-fidelity reduced-order surrogate modeling☆24Updated 2 months ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆68Updated last year
- ODIL (Optimizing a Discrete Loss) is a Python framework for solving inverse and data assimilation problems for partial differential equat …☆113Updated 3 weeks ago
- ☆70Updated last year
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆206Updated 2 years ago
- ☆103Updated last year
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆49Updated 2 years ago
- A Python package for spectral proper orthogonal decomposition (SPOD).☆109Updated this week
- Tutorials for Physics-Informed Neural Networks☆87Updated last year
- Spectral proper orthogonal decomposition in Matlab☆143Updated this week
- Introductory workshop on PINNs using the harmonic oscillator☆127Updated 3 months ago
- Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.☆42Updated this week
- MATLAB Programming for Finite Element Methods☆56Updated 2 years ago
- ☆68Updated last year
- mathLab mirror of Python Dynamic Mode Decomposition☆101Updated 5 months ago