A library for scientific machine learning and physics-informed learning

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

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

Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.

Physics-Informed Neural networks for Advanced modeling

Simple finite element assemblers

Python package for numerical derivatives and partial differential equations in any number of dimensions.

FEATool Multiphysics - "Physics Simulation Made Easy" (Fully Integrated FEA, FEniCS, OpenFOAM, SU2 Solver GUI & Engineering CAE Simulation Platform)

Perfect for developers seeking a single, unified environment for web development, backend systems, mobile apps, and competitive programming.

Source code for APDE: Create and run Processing sketches on an Android device.

The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems

A Julia package to perform Bifurcation Analysis

Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R

A framework for hydrodynamics explorations and prototyping

Castro (Compressible Astrophysics): An adaptive mesh, astrophysical compressible (radiation-, magneto-) hydrodynamics simulation code for massively parallel CPU and GPU architectures.

DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia

Linear operators for discretizations of differential equations and scientific machine learning (SciML)

TCAD Semiconductor Device Simulator

This repository containts materials for End-to-End AI for Science

BOUT++: Plasma fluid finite-difference simulation code in curvilinear coordinate systems

This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs

Automatic Finite Difference PDE solving with Julia SciML

[NeurIPS'24] Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling

PyClaw is a Python-based interface to the algorithms of Clawpack and SharpClaw. It also contains the PetClaw package, which adds parallelism through PETSc.

finite element analysis for continuum mechanics of solid bodies

Efficient Differentiable n-d PDE Solvers in JAX.

R Language Mode in Processing for Creative Coding, created by @gaocegege, maintained by @jeremydouglass

Universal modeling and simulation of fluid mechanics upon machine learning. From the Boltzmann equation, heading towards multiscale and multiphysics flows.

ETH course - Solving PDEs in parallel on GPUs I Fall 2025

Solve non-linear HJB equations.