amici
High-performance sensitivity analysis for large ordinary differential equation models
Sundials
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
DelayDiffEq
Delay differential equation (DDE) solvers in Julia for the SciML scientific machine learning ecosystem. Covers neutral and retarded delay differential equations, and differential-algebraic equations.
NeuralPDE
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
SciMLBenchmarks
Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
ImplicitDiscreteSolve
High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
DiffEqBase
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
StochasticDiffEq
Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
BoundaryValueDiffEq
Boundary value problem (BVP) solvers for scientific machine learning (SciML)
SciMLSensitivity
A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.
DiffEqFlux
Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
DifferentialEquations
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.
SciMLTutorials
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
diffeqpy
Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
DiffEqParamEstim
Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
MultiScaleArrays
A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations
DiffEqPhysics
A library for building differential equations arising from physical problems for physics-informed and scientific machine learning (SciML)
DiffEqFinancial
Differential equation problem specifications and scientific machine learning for common financial models
FEniCS
A scientific machine learning (SciML) wrapper for the FEniCS Finite Element library in the Julia programming language
SciMLExpectations
Fast uncertainty quantification for scientific machine learning (SciML) and differential equations
DASKR
Interface to DASKR, a differential algebraic system solver for the SciML scientific machine learning ecosystem
DASSL
Solves stiff differential algebraic equations (DAE) using variable stepsize backwards finite difference formula (BDF) in the SciML scientific machine learning organization
BVProblemLibrary
A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools