Optimization functions for Julia

Forward Mode Automatic Differentiation for Julia

Statically sized arrays for Julia

Julia implementation of Data structures

A benchmarking framework for the Julia language

Basic statistics for Julia

Types with default field values, keyword constructors and (un-)pack macros

A data structure for mathematical optimization problems

Special mathematical functions in Julia

Root finding functions for Julia

JSON parsing and printing

MacroTools provides a library of tools for working with Julia code and expressions.

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.

Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support

Reduce time-to-first-execution of Julia code

Lazy code loading for Julia

Julia bindings for various mathematical libraries (including flint2)

Julia package for lazily representing matrices filled with a single entry

Update immutable data

Generic abstract algebra functionality in pure Julia (no C dependencies)

Compatibility across Julia versions

Project Preferences Package

Line search methods for optimization and root-finding

Extensions for Julia's docsystem.

Fast parsing machinery for basic types in Julia

Uniform Interface for positive definite matrices of various structures

Julia implementation of associative containers that preserve insertion order

SparseArrays.jl is a Julia stdlib

Simple, consistent interfaces for any codec.

`@pack!` and `@unpack` macros

A simple shared suite of common derivative definitions

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

Missing value support for Julia

Julia math built-ins which return NaN and accumulator functions which ignore NaN

Extra sorting algorithms extending Julia's sorting API

Zlib codecs for TranscodingStreams.jl.

Interface for arithmetics on mutable types in Julia

A performant, 100% native-julia SHA1, SHA2, and SHA3 implementation

Positive-definite "approximations" to matrices

Naïve combined subexpression elimination in Julia