SciML/MethodOfLines.jl

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

Grid-based approximation of partial differential equations in Julia

Python package for solving partial differential equations using finite differences.

Tools for building fast, hackable, pseudospectral partial differential equation solvers on periodic domains

Solution of nonlinear multiphysics partial differential equation systems using the Voronoi finite volume method

Firedrake is an automated system for the portable solution of partial differential equations using the finite element method (FEM)

A Library for Advanced Neural PDE Solvers.

FiPy is a Finite Volume PDE solver written in Python

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.