AmeyaJagtap / XPINNsLinks
Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonlinear Partial Differential Equations
☆238Updated 2 years ago
Alternatives and similar repositories for XPINNs
Users that are interested in XPINNs are comparing it to the libraries listed below
Sorting:
- ☆241Updated 4 years ago
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆159Updated 5 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆270Updated 4 years ago
- PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations☆131Updated 3 months ago
- ☆168Updated 3 years ago
- PINN in solving Navier–Stokes equation☆125Updated 5 years ago
- Deep learning for Engineers - Physics Informed Deep Learning☆361Updated 2 years ago
- Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube proble…☆204Updated 2 years ago
- ☆199Updated last year
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆76Updated 2 years ago
- A place to share problems solved with SciANN☆303Updated 2 years ago
- A Physics-Informed Neural Network to solve 2D steady-state heat equations.☆172Updated 5 months ago
- Physics Informed Neural Network (PINN) for the wave equation.☆200Updated 5 years ago
- ☆117Updated 11 months ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆107Updated 3 years ago
- physics-informed neural network for elastodynamics problem☆153Updated 4 years ago
- IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.☆243Updated last year
- Here I will try to implement the solution of PDEs using PINN on pytorch for educational purpose☆57Updated 3 years ago
- Characterizing possible failure modes in physics-informed neural networks.☆148Updated 4 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆168Updated last year
- Tutorials on deep learning, Python, and dissipative particle dynamics☆206Updated 3 years ago
- Geometry-Aware Fourier Neural Operator (Geo-FNO)☆302Updated 7 months ago
- ☆110Updated 4 years ago
- ☆383Updated 3 years ago
- TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).☆265Updated 2 years ago
- Physics-informed neural network for solving fluid dynamics problems☆263Updated 5 years ago
- A pytorch implementaion of physics informed neural networks for two dimensional NS equation☆190Updated last year
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆92Updated 5 years ago
- A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks☆98Updated 3 years ago
- ☆115Updated last year