PredictiveIntelligenceLab / MultiscalePINNs
☆138Updated 2 years ago
Alternatives and similar repositories for MultiscalePINNs
Users that are interested in MultiscalePINNs are comparing it to the libraries listed below
Sorting:
- ☆163Updated last year
- ☆205Updated 3 years ago
- ☆93Updated 3 years ago
- Characterizing possible failure modes in physics-informed neural networks.☆134Updated 3 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆148Updated last year
- Non-adaptive and residual-based adaptive sampling for PINNs☆75Updated 2 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆227Updated 3 years ago
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆142Updated 4 years ago
- physics-informed neural network for elastodynamics problem☆138Updated 3 years ago
- gPINN: Gradient-enhanced physics-informed neural networks☆89Updated 3 years ago
- Original implementation of fast PINN optimization with RBA weights☆52Updated 3 weeks ago
- ☆53Updated 2 years ago
- Applications of PINOs☆125Updated 2 years ago
- ☆341Updated 2 years ago
- PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations☆96Updated 2 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆79Updated 2 years ago
- PINN in solving Navier–Stokes equation☆101Updated 4 years ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆191Updated 2 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆70Updated 2 years ago
- Implementation of PINNs in TensorFlow 2☆78Updated last year
- Here I will try to implement the solution of PDEs using PINN on pytorch for educational purpose☆49Updated 2 years ago
- ☆107Updated 3 months ago
- Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube proble…☆172Updated 2 years ago
- ☆128Updated 6 months ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆70Updated last year
- DeepONet & FNO (with practical extensions)☆292Updated last year
- Physics-informed learning of governing equations from scarce data☆145Updated last year
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆85Updated 4 years ago
- A pytorch implementaion of physics informed neural networks for two dimensional NS equation☆141Updated last year
- This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs☆173Updated last week