FEINN

A differentiable PDE solving framework for machine learning

Code accompanying my blog post: So, what is a physics-informed neural network?

PINNs-Torch, Physics-informed Neural Networks (PINNs) implemented in PyTorch.

Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)

PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks

A Physics Informed Neural Network made using PyTorch

IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.

开源Go语言数值算法库(An open numerical library purely based on Go programming language)

A toolkit with data-driven pipelines for physics-informed machine learning.

Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube problems and plane stress linear elasticity boundary value problems