PINA-org/PINA

A library for scientific machine learning and physics-informed learning

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods

Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

Physics Informed Machine Learning Tutorials (Pytorch and Jax)

A differentiable PDE solving framework for machine learning

Learning in infinite dimension with neural operators.

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.