Physics Informed Neural Networks Python Packages

pina-mathlab

Physics-Informed Neural networks for Advanced modeling

pinnicle

A Python library for solving ice sheet modeling problems using Physics Informed Neural Networks

jwave

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

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.

simulai-toolkit

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

pinnx

Physics-Informed Neural Networks for Scientific Machine Learning in JAX

pdebench

PDEBench: An Extensive Benchmark for Scientific Machine Learning

tensordiffeq

Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing

nops

nops: Neural Operators made simple — with physics-informed losses for FNO, DeepONet, and GNO

pinnstorch

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

promethium-seismic

Promethium - Advanced Seismic Data Recovery and Reconstruction Framework. State-of-the-art AI-driven framework for seismic signal reconstruction, denoising, and geophysical data enhancement.

idrlnet

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

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.

separable-operator-networks

Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.

pararealml

A machine learning boosted parallel-in-time differential equation solver framework

parametrix

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

fastvpinns

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

oscillink

Oscillink Lattice — Short-Term Coherence SDK (physics-inspired memory for generative models)

geoprior-v3

GeoPrior-v3: Physics-guided AI for geohazards

physdbd

Physics-based machine learning with dynamic Boltzmann distributions

pinnstf2

PINNs-TF2, Physics-informed Neural Networks (PINNs) implemented in TensorFlow V2.

frontx

⚛️ Nonlinear diffusion problems with JAX

pinnsjax

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