Julia bindings for the Enzyme automatic differentiator

Update immutable data

Calculating contour curves for 2D scalar fields in Julia

Simple, consistent interfaces for any codec.

The Base interface of the SciML ecosystem

Powerful convenience for Julia visualizations and data analysis

Primitives for construction of objects

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.

Forward Mode Automatic Differentiation for Julia

SciMLOperators.jl: Matrix-Free Operators for the SciML Scientific Machine Learning Common Interface in Julia

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

Julia implementation of Data structures

A structure interface for SciML to give queryable properties from user data and parameters

Julia macro for re-exporting one module from another

Julia wrapper for the LLVM C API

Formatted output of timed sections in Julia

Julia functional programming infrastructures and metaprogramming facilities

Basic statistics for Julia

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

Colorschemes, colormaps, gradients, and palettes

Fixed point types for julia

Reusable compiler infrastructure for Julia GPU backends.

Physical quantities with arbitrary units

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

Reduce time-to-first-execution of Julia code

Tools for writing functions that handle many kinds of IO arguments

An optimized graphs package for the Julia programming language

Compatibility across Julia versions

-

A statistics-focused namespace for packages to share functions

Extensions for Julia's docsystem.

Functions generated at runtime without world-age issues or overhead

HTTP for Julia

JSON parsing and printing

Reusable array functionality for Julia's various GPU backends.

The cheapest threads you can find!

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