Jianxun-Wang / graphGalerkin
Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems
☆47Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for graphGalerkin
- PDE Preserved Neural Network☆33Updated 4 months ago
- DeepONet extrapolation☆24Updated last year
- Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"☆34Updated last year
- ☆52Updated 2 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆19Updated last year
- Code for 'Physics-Informed Neural Networks for Shell Structures'☆30Updated 3 months ago
- Multifidelity DeepONet☆27Updated last year
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆19Updated 2 years ago
- Physics-informed radial basis network☆26Updated 6 months ago
- Sparse Physics-based and Interpretable Neural Networks☆46Updated 3 years ago
- XPINN code written in TensorFlow 2☆27Updated last year
- POD-PINN code and manuscript☆46Updated last week
- Contains implementation of PINN using Tensorflow 2.4.0☆14Updated last year
- Modified Meshgraphnets with more features☆36Updated 5 months ago
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆40Updated last year
- This repository includes the implementation of the Physics Informed Neural Network and The Deep Energy Method on 1D, 2D boundary value an…☆14Updated 2 years ago
- A method based on a feed forward neural network to solve partial differential equations in nonlinear elasticity at finite strain based on…☆51Updated 2 years ago
- MIONet: Learning multiple-input operators via tensor product☆27Updated 2 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆55Updated 7 months ago
- ☆94Updated 4 months ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆82Updated 3 years ago
- Physics-informed neural networks for identifying material properties in solid mechanics☆14Updated last year
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆80Updated last year
- ☆16Updated 9 months ago
- Non-adaptive and residual-based adaptive sampling for PINNs☆58Updated 2 years ago
- Code repo for Fluid Graph Network☆22Updated 2 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆28Updated 4 months ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆58Updated last year
- Physics-informed neural networks for two-phase flow problems☆48Updated last year
- Physics-guided neural network framework for elastic plates☆32Updated 2 years ago