A Julia package for probability distributions and associated functions.

Forward Mode Automatic Differentiation for Julia

Statically sized arrays for Julia

Macro(s) for vectorizing loops.

Julia implementation of Data structures

Basic statistics for Julia

A Julia package for evaluating distances (metrics) between vectors.

High performance nearest neighbor data structures (KDTree and BallTree) and algorithms for Julia.

Save and load data in the HDF5 file format from Julia

MPI wrappers for Julia

A Julia package for data clustering

Special mathematical functions in Julia

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

Adaptive 1d numerical Gauss–Kronrod integration in Julia

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.

Mathematical functions related to statistics.

Reduce time-to-first-execution of Julia code

Lazy code loading for Julia

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

Julia package for lazily representing matrices filled with a single entry

Julia macro for re-exporting one module from another

Compatibility across Julia versions

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

Project Preferences Package

Extensions for Julia's docsystem.

A Julia clone of https://pypi.python.org/pypi/tqdm

Uniform Interface for positive definite matrices of various structures

Julia implementation of associative containers that preserve insertion order

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SparseArrays.jl is a Julia stdlib

`@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

A Julia package for calculating hypergeometric functions

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

Ask the CPU for cache sizes, SIMD feature support, a running hypervisor, and more.

Extra sorting algorithms extending Julia's sorting API

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

Static types useful for dispatch and generated functions.