Prime numbers in Julia

Random Number Generators for the Julia Language.

The Arnoldi Method with Krylov-Schur restart, natively in Julia.

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

Fast and differentiable implementations of matrix exponentials, Krylov exponential matrix-vector multiplications ("expmv"), KIOPS, ExpoKit functions, and more. All your exponential needs in SciML form.

Julia implementation of associative containers that preserve insertion order

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Lazy in-place transformations of arrays

Robust implementation for random-walk Metropolis-Hastings algorithms

SparseArrays.jl is a Julia stdlib

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

Basic interface for manifolds in Julia

A general-purpose toolbox for efficient Kronecker-based algebra.

Collective tools for metaprogramming on Julia Expr

Simple, consistent interfaces for any codec.

Cunning tricks though the julia compiler internals

`@pack!` and `@unpack` macros

A CommonMark-compliant Markdown parser for Julia.

Solution of Lyapunov, Sylvester and Riccati matrix equations using Julia

A simple index type that allows for inverted selections

Abstract types and interfaces for Markov chain Monte Carlo methods

Fixed point types for julia

TAR files: create, list, extract them in pure Julia

Implementation of variational Bayes inference algorithms

Light-weight expression manipulation tools

Basic color definitions and traits

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A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications

A simple shared suite of common derivative definitions

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Julia package for various special functions based on `log` and `exp`.

A Julia package for describing domains as continuous sets of elements

Optimisers.jl defines many standard optimisers and utilities for learning loops.

Missing value support for Julia

A Julia package for calculating hypergeometric functions

Base library providing vectorization-tools (ie, SIMD) that other libraries are built off of.

Fast and simple nonlinear solvers for the SciML common interface. Newton, Broyden, Bisection, Falsi, and more rootfinders on a standard interface.

A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)