Pinn Python Packages

deepxde

A library for scientific machine learning and physics-informed learning

anypinn

🤖 A modular and flexible solution to build Physics-Informed Neural Networks (PINNs) for any mathematical problem.

pina-mathlab

Physics-Informed Neural networks for Advanced modeling

dedekind

Dedekind is a high-performance, differentiable programming language for scientific computing and machine learning. It features compile-time physical units, automatic differentiation, built-in solvers, and GPU/TPU acceleration.

parametrix

🪄 Flax-like computed parameters for bare JAX (and Equinox)

pinnx

Physics-Informed Neural Networks for Scientific Machine Learning in JAX.

neurodiffeq

A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.

reactor-twin

Physics-constrained Neural DEs for chemical reactor digital twins

fast-poisson-solver

The Poisson equation is an integral part of many physical phenomena, yet its computation is often time-consuming. This module presents an efficient method using physics-informed neural networks (PINNs) to rapidly solve arbitrary 2D Poisson problems.

fastvpinns

FastVPINNs - A tensor-driven acceleration of VPINNs for complex geometries

kbeta

Kourkoutas-β optimiser and demo workloads

kbeta-pinn3d

3-D cylindrical PINN benchmark for the Kourkoutas-β optimizer paper

frontx

Nonlinear diffusion problems with JAX