Dependency Packages

SparseDiffTools.jl201Fast jacobian computation through sparsity exploitation and matrix coloring

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

LinearSolve.jl178LinearSolve.jl: HighPerformance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.

Plots.jl1710Powerful convenience for Julia visualizations and data analysis

GPUArrays.jl270Reusable array functionality for Julia's various GPU backends.

YAML.jl101Parse yer YAMLs

BandedMatrices.jl129A Julia package for representing banded matrices

SciMLOperators.jl30SciMLOperators.jl: MatrixFree Operators for the SciML Scientific Machine Learning Common Interface in Julia

QuadGK.jl210Adaptive 1d numerical Gaussâ€“Kronrod integration in Julia

Distributions.jl987A Julia package for probability distributions and associated functions.

Cthulhu.jl456The slow descent into madness

HTTP.jl592HTTP for Julia

Makie.jl1978Visualizations and plotting in Julia

SimpleBufferStream.jl4What Base.BufferStream should be

AbstractFFTs.jl96A Julia framework for implementing FFTs

ChainRulesCore.jl218ADbackend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for your functions in your packages, without depending on any particular AD system.

FillArrays.jl143Julia package for lazily representing matrices filled with a single entry

NonlinearSolve.jl112Highperformance and differentiationenabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and NewtonKrylov support.

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

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.

ForwardDiff.jl778Forward Mode Automatic Differentiation for Julia

Combinatorics.jl204A combinatorics library for Julia

KrylovKit.jl203Krylov methods for linear problems, eigenvalues, singular values and matrix functions

JuliaSyntax.jl218A Julia frontend, written in Julia

ArrayInterface.jl125Designs for new Base array interface primitives, used widely through scientific machine learning (SciML) and other organizations

Tables.jl264An interface for tables in Julia

PrecompileTools.jl128Reduce timetofirstexecution of Julia code

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

GR.jl342Plotting for Julia based on GR, a framework for visualisation applications

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

LaTeXStrings.jl184Convenient input and display of LaTeX equation strings for the Julia language

ColorVectorSpace.jl32Treat colors as if they are nvectors for the purposes of arithmetic

MutableArithmetics.jl45Interface for arithmetics on mutable types in Julia

Scratch.jl45Scratch spaces for all your persistent mutable data needs

Optim.jl960Optimization functions for Julia

Parsers.jl98Fast parsing machinery for basic types in Julia

FiniteDiff.jl202Fast nonallocating calculations of gradients, Jacobians, and Hessians with sparsity support

IterativeSolvers.jl358Iterative algorithms for solving linear systems, eigensystems, and singular value problems

StaticArrays.jl643Statically sized arrays for Julia

LLVM.jl109Julia wrapper for the LLVM C API
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