Package to call Python functions from the Julia language

A Julia package for probability distributions and associated functions.

Forward Mode Automatic Differentiation for Julia

Statically sized arrays for Julia

Julia implementation of Data structures

Basic statistics for Julia

Plotting for Julia based on matplotlib.pyplot

Save and load data in the HDF5 file format from Julia

MPI wrappers for Julia

Special mathematical functions in Julia

Simple curve fitting in Julia

JSON parsing and printing

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

Julia module for reading MATLAB files

Calculus functions in Julia

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.

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

Mathematical functions related to statistics.

Package for parsing command-line arguments to Julia programs.

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

Lazy code loading for Julia

Julia package for lazily representing matrices filled with a single entry

Conda managing Julia binary dependencies

Julia macro for re-exporting one module from another

Compatibility across Julia versions

Project Preferences Package

Fast parsing machinery for basic types in Julia

Extensions for Julia's docsystem.

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

Simple, consistent interfaces for any codec.

Fixed point types for julia

Basic color definitions and traits

A simple shared suite of common derivative definitions

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