Dependency Packages
-
Enzyme.jl438Julia bindings for the Enzyme automatic differentiator
-
Accessors.jl175Update immutable data
-
Symbolics.jl1353Symbolic programming for the next generation of numerical software
-
SymbolicUtils.jl537Symbolic expressions, rewriting and simplification
-
OrdinaryDiffEq.jl533High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
-
Contour.jl44Calculating contour curves for 2D scalar fields in Julia
-
LinearSolve.jl244LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.
-
TranscodingStreams.jl85Simple, consistent interfaces for any codec.
-
SciMLBase.jl130The Base interface of the SciML ecosystem
-
Plots.jl1825Powerful convenience for Julia visualizations and data analysis
-
ConstructionBase.jl34Primitives for construction of objects
-
ChainRulesCore.jl253AD-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.
-
ForwardDiff.jl888Forward Mode Automatic Differentiation for Julia
-
SciMLOperators.jl42SciMLOperators.jl: Matrix-Free Operators for the SciML Scientific Machine Learning Common Interface in Julia
-
Latexify.jl558Convert julia objects to LaTeX equations, arrays or other environments.
-
DataStructures.jl690Julia implementation of Data structures
-
DifferentiationInterface.jl163An interface to various automatic differentiation backends in Julia.
-
SciMLStructures.jl7A structure interface for SciML to give queryable properties from user data and parameters
-
Reexport.jl162Julia macro for re-exporting one module from another
-
LLVM.jl130Julia wrapper for the LLVM C API
-
TimerOutputs.jl651Formatted output of timed sections in Julia
-
MLStyle.jl402Julia functional programming infrastructures and metaprogramming facilities
-
DelayDiffEq.jl59Delay differential equation (DDE) solvers in Julia for the SciML scientific machine learning ecosystem. Covers neutral and retarded delay differential equations, and differential-algebraic equations.
-
Sparspak.jl37Direct solution of large sparse systems of linear algebraic equations in pure Julia
-
StatsFuns.jl232Mathematical functions related to statistics.
-
AbstractTrees.jl200Abstract julia interfaces for working with trees
-
StatsBase.jl584Basic statistics for Julia
-
CommonSolve.jl19A common solve function for scientific machine learning (SciML) and beyond
-
ADTypes.jl38Repository for automatic differentiation backend types
-
Format.jl37A Julia package to provide C and Python-like formatting support
-
DiffEqBase.jl309The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
-
BlockArrays.jl194BlockArrays for Julia
-
ColorSchemes.jl187Colorschemes, colormaps, gradients, and palettes
-
FixedPointNumbers.jl79Fixed point types for julia
-
NonlinearSolve.jl227High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
-
GPUCompiler.jl156Reusable compiler infrastructure for Julia GPU backends.
-
Unitful.jl603Physical quantities with arbitrary units
-
SymbolicLimits.jl3-
-
EnumX.jl87This is what I wish `Base.@enum` was.
-
LoopVectorization.jl742Macro(s) for vectorizing loops.
Loading more...