Powerful convenience for Julia visualizations and data analysis

Symbolic programming for the next generation of numerical software

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

Physical quantities with arbitrary units

Basic statistics for Julia

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

HDF5-compatible file format in pure Julia

Symbolic expressions, rewriting and simplification

Fast, continuous interpolation of discrete datasets in Julia

Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration.

An optimized graphs package for the Julia programming language

Julia bindings for the Enzyme automatic differentiator

A Julia package for evaluating distances (metrics) between vectors.

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

Julia functional programming infrastructures and metaprogramming facilities

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

Special mathematical functions in Julia

Root finding functions for Julia

A Julia Basket of Hand-Picked Krylov Methods

Julia solvers for systems of nonlinear equations and mixed complementarity problems

Efficient implementation of struct arrays in Julia

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.

Lazy arrays and linear algebra in Julia

An interface for tables in Julia

Calculus functions in Julia

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.

Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support

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

The cheapest threads you can find!

Fast jacobian computation through sparsity exploitation and matrix coloring

Mathematical functions related to statistics.