General Differential Equations Packages

Makhno.jl0Spectral element code implemented in Julia

WiltonInts84.jl0Integrals of arbitrary powers of R over flat triangles

MovcolN.jl0Moving collocation method to solve one dimensional partial differential equations

HPFEM.jl1HP Finite elements in Julia

RiemannHilbert.jl5A Julia package for solving Riemann–Hilbert problems

OperatorLearning.jl37No need to train, he's a smooth operator

DiffEqProblemLibrary.jl39A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools

GeometricIntegrators.jl42Geometric Numerical Integration in Julia

DiffEqDevTools.jl43Benchmarking, testing, and development tools for differential equations and scientific machine learning (SciML)

DelayDiffEq.jl46Delay differential equation (DDE) solvers in Julia for the SciML scientific machine learning ecosystem. Covers neutral and retarded delay differential equations, and differentialalgebraic equations.

DiffEqParamEstim.jl51Easy scientific machine learning (SciML) parameter estimation with prebuilt loss functions

SingularSpectrumAnalysis.jl51A package for performing Singular Spectrum Analysis (SSA) and timeseries decomposition

DiffEqCallbacks.jl52A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers

DiffEqNoiseProcess.jl55A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)

SingularIntegralEquations.jl57Julia package for solving singular integral equations

DiffEqUncertainty.jl59Fast uncertainty quantification for scientific machine learning (SciML) and differential equations

HighDimPDE.jl60A Julia package that breaks down the curse of dimensionality in solving PDEs.

FractionalDiffEq.jl62Solve Fractional Differential Equations using high performance numerical methods

StructuralIdentifiability.jl63Fast and automatic structural identifiability software for ODE systems

Kalman.jl69Flexible filtering and smoothing in Julia

ParameterizedFunctions.jl72A simple domainspecific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications

EconPDEs.jl91Solve forwardlooking PDEs (e.g. HJB equations).

ODEFilters.jl100Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing

ProbNumDiffEq.jl100Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing

ODE.jl101Assorted basic Ordinary Differential Equation solvers for scientific machine learning (SciML). Deprecated: Use DifferentialEquations.jl instead.

MethodOfLines.jl118Automatic Finite Difference PDE solving with Julia SciML

ReachabilityAnalysis.jl170Methods to compute sets of states reachable by dynamical systems

Sundials.jl188Julia 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

StochasticDiffEq.jl200Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem

ComponentArrays.jl231Arrays with arbitrarily nested named components.

StateSpaceModels.jl235StateSpaceModels.jl is a Julia package for timeseries analysis using statespace models.

DiffEqBase.jl243The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems

DiffEqSensitivity.jl248A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimizethendiscretize, discretizethenoptimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.

DiffEqOperators.jl279Linear operators for discretizations of differential equations and scientific machine learning (SciML)

OrdinaryDiffEq.jl425High performance ordinary differential equation (ODE) and differentialalgebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

DynamicalSystems.jl725Award winning software library for nonlinear dynamics and nonlinear timeseries analysis

DifferentialEquations.jl2503Multilanguage suite for highperformance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differentialalgebraic equations (DAEs), and more in Julia.
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