ADharaUTEXAS123007 / FNOLinks
Fourier_neural_operator
☆14Updated 2 years ago
Alternatives and similar repositories for FNO
Users that are interested in FNO are comparing it to the libraries listed below
Sorting:
- DeepONet & FNO (with practical extensions)☆303Updated last year
- Non-adaptive and residual-based adaptive sampling for PINNs☆78Updated 2 years ago
- ☆43Updated 2 years ago
- A pytorch implementaion of physics informed neural networks for two dimensional NS equation☆146Updated last year
- ☆345Updated 2 years ago
- ☆165Updated last year
- physics-informed neural network for elastodynamics problem☆140Updated 3 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆229Updated 3 years ago
- ☆28Updated last year
- PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations☆99Updated 2 years ago
- ☆131Updated 7 months ago
- PINN in solving Navier–Stokes equation☆102Updated 5 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆78Updated 2 years ago
- Geometry-Aware Fourier Neural Operator (Geo-FNO)☆258Updated this week
- ☆141Updated 2 years ago
- gPINN: Gradient-enhanced physics-informed neural networks☆91Updated 3 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆150Updated last year
- ☆210Updated 3 years ago
- This is the code of my master thesis.☆124Updated last month
- Physics Informed Neural Network (PINN) for the wave equation.☆170Updated 4 years ago
- DeepXDE and PINN☆112Updated 3 years ago
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆146Updated 4 years ago
- Characterizing possible failure modes in physics-informed neural networks.☆135Updated 3 years ago
- U-FNO - an enhanced Fourier neural operator-based deep-learning model for multiphase flow☆136Updated 9 months ago
- ☆50Updated 5 months ago
- Implementation of PINNs in TensorFlow 2☆78Updated last year
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆70Updated 2 years ago
- hPINN: Physics-informed neural networks with hard constraints☆133Updated 3 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆55Updated 4 years ago
- Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube proble…☆176Updated 2 years ago