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

A combinatorics library for Julia

Tools for easily handling objects like arrays of arrays and deeper nestings in scientific machine learning (SciML) and other applications

Convenient input and display of LaTeX equation strings for the Julia language

Color manipulation utilities for Julia

Reduce time-to-first-execution of Julia code

Abstract julia interfaces for working with trees

Lazy code loading for Julia

Fortran-like arrays with arbitrary, zero or negative starting indices.

BlockArrays for Julia

Colorschemes, colormaps, gradients, and palettes

Julia package for lazily representing matrices filled with a single entry

Update immutable data

＠memoize macro for Julia

Update deeply nested immutable structs.

An interface to various automatic differentiation backends in Julia.

Julia macro for re-exporting one module from another

Reusable compiler infrastructure for Julia GPU backends.

Simple Traits for Julia

An enhancement to julia piping syntax

Colored and styled strings for terminals.

Compatibility across Julia versions

Build and simulate jump equations like Gillespie simulations and jump diffusions with constant and state-dependent rates and mix with differential equations and scientific machine learning (SciML)

Composable Loggers for the Julia Logging StdLib

The dispatch doctor prescribes type stability

Multivariate polynomials interface

Designs for new Base array interface primitives, used widely through scientific machine learning (SciML) and other organizations

Efficient and type-stable physical quantities in Julia

Julia wrapper for the LLVM C API

The Base interface of the SciML ecosystem

Project Preferences Package

A Julia package for representing banded matrices

Posix-compliant file name pattern matching

Themes for the Julia plotting package Plots.jl

Arrays which also have a label for each element for easy scientific machine learning (SciML)

Parameterise all the things

Line search methods for optimization and root-finding

Extensions for Julia's docsystem.

Fast parsing machinery for basic types in Julia

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