27 Open Source Differentialequations Software Projects

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components

Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

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

Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization

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

High performance differential equation solvers for ordinary differential equations, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

Julia interface to Sundials, including a nonlinear solver (KINSOL), ODE's (CVODE and ARKODE), and DAE's (IDA) in a SciML scientific machine learning enabled manner

Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem

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

Benchmarks for scientific machine learning (SciML) software and differential equation solvers

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

GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, and more for ODEs, SDEs, DDEs, DAEs, etc.

Arrays with arbitrarily nested named components.

Automatic detection of sparsity in pure Julia functions for sparsity-enabled scientific machine learning (SciML)

A scientific machine learning (SciML) wrapper for the FEniCS Finite Element library in the Julia programming language

A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations

Advanced Multilanguage Interface to CVODES and IDAS

A library for building differential equations arising from physical problems for physics-informed and scientific machine learning (SciML)

Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions

Uncertainty quantification for scientific machine learning (SciML) and differential equations

Solves stiff differential algebraic equations (DAE) using variable stepsize backwards finite difference formula (BDF) in the SciML scientific machine learning organization

Delay differential equation solvers for the SciML scientific machine learning ecosystem

Differential equation problem specifications and scientific machine learning for common financial models

Boundary value problem (BVP) solvers for scientific machine learning (SciML)

A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools

Monte Carlo simulation routines for high-performance parallelization of differential equation solvers and scientific machine learning