Powerful convenience for Julia visualizations and data analysis

Optimization functions for Julia

A Julia package for probability distributions and associated functions.

Forward Mode Automatic Differentiation for Julia

Statically sized arrays for Julia

Macro(s) for vectorizing loops.

Julia implementation of Data structures

Formatted output of timed sections in Julia

HTTP for Julia

A benchmarking framework for the Julia language

Physical quantities with arbitrary units

Basic statistics for Julia

A Julia package for disciplined convex programming

Convert julia objects to LaTeX equations, arrays or other environments.

HDF5-compatible file format in pure Julia

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

Fast, continuous interpolation of discrete datasets in Julia

An optimized graphs package for the Julia programming language

Julia bindings for the Enzyme automatic differentiator

Types with default field values, keyword constructors and (un-)pack macros

Julia functional programming infrastructures and metaprogramming facilities

A data structure for mathematical optimization problems

Save and load data in the HDF5 file format from Julia

MPI wrappers for Julia

Heterogeneous programming in Julia

Plotting for Julia based on GR, a framework for visualisation applications

Special mathematical functions in Julia

Taylor polynomial expansions in one and several independent variables.

A Julia Basket of Hand-Picked Krylov Methods

Reusable array functionality for Julia's various GPU backends.

JSON parsing and printing

MacroTools provides a library of tools for working with Julia code and expressions.

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

Lazy arrays and linear algebra in Julia

An interface for tables in Julia

Julia package for Gaussian quadrature

Krylov methods for linear problems, eigenvalues, singular values and matrix functions

Julia bindings to the FFTW library for fast Fourier transforms

Adaptive 1d numerical Gauss–Kronrod integration in Julia

AD-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.