erfanhamdi / pinn-torch
Here I will try to implement the solution of PDEs using PINN on pytorch for educational purpose
☆47Updated 2 years ago
Alternatives and similar repositories for pinn-torch:
Users that are interested in pinn-torch are comparing it to the libraries listed below
- PINN in solving Navier–Stokes equation☆93Updated 4 years ago
- Non-adaptive and residual-based adaptive sampling for PINNs☆65Updated 2 years ago
- Implementation of PINNs in TensorFlow 2☆75Updated last year
- Physics Informed Neural Networks (based on Raissi et al) extended to three dimensions on the heat diffusion equations☆16Updated 2 years ago
- Physics-informed neural networks for two-phase flow problems☆52Updated 2 years ago
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆135Updated 4 years ago
- A pytorch implementaion of physics informed neural networks for two dimensional NS equation☆132Updated 11 months ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆51Updated 4 years ago
- physics-informed neural network for elastodynamics problem☆132Updated 3 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆22Updated 2 years ago
- Basic implementation of physics-informed neural network with pytorch.☆63Updated 2 years ago
- PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations☆88Updated 2 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆68Updated 11 months ago
- Original implementation of fast PINN optimization with RBA weights☆49Updated 5 months ago
- ☆106Updated last month
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆63Updated 3 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆66Updated 2 years ago
- ☆44Updated 3 months ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆43Updated 10 months ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆67Updated last year
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆31Updated 3 years ago
- gPINN: Gradient-enhanced physics-informed neural networks☆84Updated 2 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆146Updated 10 months ago
- ☆130Updated 2 years ago
- Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube proble…☆169Updated 2 years ago
- ☆115Updated 5 months ago
- ☆157Updated last year
- Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.☆36Updated last week
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆67Updated 2 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆84Updated 4 years ago