pinnx

A library for scientific machine learning and physics-informed 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)

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

A large-scale benchmark for machine learning methods in fluid dynamics

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

A JAX-based research framework for differentiable and parallelizable acoustic simulations, on CPU, GPUs and TPUs

Neural network based solvers for partial differential equations and inverse problems :milky_way:. Implementation of physics-informed neural networks in pytorch.