Parse yer YAMLs

A Julia package for representing banded matrices

Themes for the Julia plotting package Plots.jl

Parameterise all the things

Line search methods for optimization and root-finding

Fast parsing machinery for basic types in Julia

Extensions for Julia's docsystem.

Tools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes

Uniform Interface for positive definite matrices of various structures

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Functions generated at runtime without world-age issues or overhead

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

A Julia Protocol for Geospatial Data

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SparseArrays.jl is a Julia stdlib

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

Simple, consistent interfaces for any codec.

Cunning tricks though the julia compiler internals

Collective tools for metaprogramming on Julia Expr

`@pack!` and `@unpack` macros

A simple index type that allows for inverted selections

Fixed point types for julia

IO for Meshes

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

Light-weight expression manipulation tools

Basic color definitions and traits

🏩🏠🌆🏨🌇🏦

A simple shared suite of common derivative definitions

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

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.

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