isds-neu / PhyCRNetLinks
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
☆168Updated last year
Alternatives and similar repositories for PhyCRNet
Users that are interested in PhyCRNet are comparing it to the libraries listed below
Sorting:
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆270Updated 4 years ago
- A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks☆98Updated 3 years ago
- ☆196Updated last year
- PINN in solving Navier–Stokes equation☆125Updated 5 years ago
- ☆168Updated 3 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆107Updated 3 years ago
- Here I will try to implement the solution of PDEs using PINN on pytorch for educational purpose☆57Updated 3 years ago
- A pytorch implementaion of physics informed neural networks for two dimensional NS equation☆190Updated last year
- ☆69Updated 3 years ago
- physics-informed neural network for elastodynamics problem☆153Updated 4 years ago
- DeepXDE and PINN☆149Updated 3 years ago
- PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations☆132Updated 3 months ago
- This is the code of my master thesis.☆183Updated 9 months ago
- Physics-informed learning of governing equations from scarce data☆167Updated 2 years ago
- Original implementation of fast PINN optimization with RBA weights☆69Updated 4 months ago
- ☆117Updated last year
- ☆199Updated last year
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆159Updated 5 years ago
- Physics-encoded recurrent convolutional neural network☆48Updated 4 years ago
- Physics-informed neural network for solving fluid dynamics problems☆263Updated 5 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆92Updated last year
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆92Updated 5 years ago
- We introduce an innovative physics-informed LSTM framework for metamodeling of nonlinear structural systems with scarce data.☆99Updated 2 years ago
- Implementing a physics-informed DeepONet from scratch☆56Updated 2 years ago
- Basic implementation of physics-informed neural network with pytorch.☆87Updated 3 years ago
- U-FNO - an enhanced Fourier neural operator-based deep-learning model for multiphase flow☆164Updated last year
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆77Updated 2 years ago
- ☆241Updated 4 years ago
- Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube proble…☆206Updated 2 years ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆75Updated last year