Basic statistics for Julia

A data structure for mathematical optimization problems

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

Colorschemes, colormaps, gradients, and palettes

Fixed point types for julia

C-style interface to the libcfitsio library.

Reusable compiler infrastructure for Julia GPU backends.

A benchmarking framework for the Julia language

Physical quantities with arbitrary units

-

Immutables as mutables, mutables as immutables.

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

Archive of functions that emulate R's d-p-q-r functions for probability distributions

Solution of Lyapunov, Sylvester and Riccati matrix equations using Julia

A Julia package for probability distributions and associated functions.

An optimized graphs package for the Julia programming language

A Julia package for calculating hypergeometric functions

Reproducible data setup for reproducible science

Compatibility across Julia versions

-

A statistics-focused namespace for packages to share functions

Extensions for Julia's docsystem.

Package for checking function arguments

Positive-definite "approximations" to matrices

Implementation of normalising flows and constrained random variable transformations

Types and utility functions for summarizing Markov chain Monte Carlo simulations

Functions generated at runtime without world-age issues or overhead

HTTP for Julia

AD backends for LogDensityProblems.jl.

JSON parsing and printing

Save and load data in the HDF5 file format from Julia

Progress meter for long-running computations

Adaptive 1d numerical Gauss–Kronrod integration in Julia

Reusable array functionality for Julia's various GPU backends.

Julia package for lazily representing matrices filled with a single entry

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