Optimization functions for Julia

Basic statistics for Julia

A data structure for mathematical optimization problems

A common solve function for scientific machine learning (SciML) and beyond

Repository for automatic differentiation backend types

A Julia package to provide C and Python-like formatting support

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

BlockArrays for Julia

Colorschemes, colormaps, gradients, and palettes

Fixed point types for julia

High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.

Reusable compiler infrastructure for Julia GPU backends.

A benchmarking framework for the Julia language

Physical quantities with arbitrary units

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This is what I wish `Base.@enum` was.

Macro(s) for vectorizing loops.

Reduce time-to-first-execution of Julia code

Tools for writing functions that handle many kinds of IO arguments

Archive of functions that emulate R's d-p-q-r functions for probability distributions

A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers

Solution of Lyapunov, Sylvester and Riccati matrix equations using Julia

A Julia package for probability distributions and associated functions.

An optimized graphs package for the Julia programming language

A Julia package for calculating hypergeometric functions

Compatibility across Julia versions

Posix-compliant file name pattern matching

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A statistics-focused namespace for packages to share functions

Extensions for Julia's docsystem.

Fast jacobian computation through sparsity exploitation and matrix coloring

Positive-definite "approximations" to matrices

Functions generated at runtime without world-age issues or overhead

HTTP for Julia

Coloring algorithms for sparse Jacobian and Hessian matrices

JSON parsing and printing

Progress meter for long-running computations

Adaptive 1d numerical Gauss–Kronrod integration in Julia

Reusable array functionality for Julia's various GPU backends.

The cheapest threads you can find!