Dependency Packages
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SparseDiffTools.jl201Fast jacobian computation through sparsity exploitation and matrix coloring
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LinearSolve.jl178LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.
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Plots.jl1710Powerful convenience for Julia visualizations and data analysis
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GPUArrays.jl270Reusable array functionality for Julia's various GPU backends.
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CSV.jl405Utility library for working with CSV and other delimited files in the Julia programming language
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YAML.jl101Parse yer YAMLs
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DataFrames.jl1593In-memory tabular data in Julia
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SciMLOperators.jl30SciMLOperators.jl: Matrix-Free Operators for the SciML Scientific Machine Learning Common Interface in Julia
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JuMP.jl1956Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
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QuadGK.jl210Adaptive 1d numerical Gauss–Kronrod integration in Julia
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CoordinateTransformations.jl158A fresh approach to coordinate transformations...
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Distributions.jl987A Julia package for probability distributions and associated functions.
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Cthulhu.jl456The slow descent into madness
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HTTP.jl592HTTP for Julia
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IJulia.jl2629Julia kernel for Jupyter
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SimpleBufferStream.jl4What Base.BufferStream should be
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CategoricalArrays.jl118Arrays for working with categorical data (both nominal and ordinal)
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AbstractFFTs.jl96A Julia framework for implementing FFTs
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ChainRulesCore.jl218AD-backend 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.
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KernelDensity.jl150Kernel density estimators for Julia
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FillArrays.jl143Julia package for lazily representing matrices filled with a single entry
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NonlinearSolve.jl112High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
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OrdinaryDiffEq.jl425High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
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InlineStrings.jl35Fixed-width string types for Julia
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ForwardDiff.jl778Forward Mode Automatic Differentiation for Julia
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KrylovKit.jl203Krylov methods for linear problems, eigenvalues, singular values and matrix functions
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JuliaSyntax.jl218A Julia frontend, written in Julia
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ArrayInterface.jl125Designs for new Base array interface primitives, used widely through scientific machine learning (SciML) and other organizations
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Tables.jl264An interface for tables in Julia
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PrecompileTools.jl128Reduce time-to-first-execution of Julia code
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GR.jl342Plotting for Julia based on GR, a framework for visualisation applications
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DiffEqBase.jl243The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
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VersionParsing.jl13Flexible VersionNumber parsing in Julia
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SoftGlobalScope.jl26Utilities for "soft" global scope in interactive Julia environments
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LaTeXStrings.jl184Convenient input and display of LaTeX equation strings for the Julia language
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ColorVectorSpace.jl32Treat colors as if they are n-vectors for the purposes of arithmetic
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MutableArithmetics.jl45Interface for arithmetics on mutable types in Julia
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Scratch.jl45Scratch spaces for all your persistent mutable data needs
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Optim.jl960Optimization functions for Julia
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Clustering.jl311A Julia package for data clustering
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