An efficient sampler for discrete random variables

The Arnoldi Method with Krylov-Schur restart, natively 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.

Interface for transformation functions in Julia

Color manipulation utilities for Julia

Basic color definitions and traits

A combinatorics library for Julia

Compatibility across Julia versions

Declarative vector graphics

A data-focused namespace for packages to share functions

Julia implementation of Data structures

Interface for mathematical/statistical densities in Julia

Value iteration solver for MDPs

Create and control multiple Julia processes remotely for distributed computing. Ships as a Julia stdlib.

A Julia package for probability distributions and associated functions.

Extensions for Julia's docsystem.

Julia package for lazily representing matrices filled with a single entry

Fixed point types for julia

An optimized graphs package for the Julia programming language

A Julia package for calculating hypergeometric functions

Julia implementation of zlib decompression

Interface for function inversion in Julia

Defines additional irrationals

Common functional iterator patterns

JSON parsing and printing

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

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

Unified measure and coordinates types

Missing value support for Julia

Some utilities for working with NamedTuples

Julia implementation of associative containers that preserve insertion order

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

Fast parsing machinery for basic types in Julia

Simple particle filter implementation in Julia - works with POMDPs.jl models or others.

Uniform Interface for positive definite matrices of various structures

Tools to help develop POMDP Models

MDPs and POMDPs in Julia - An interface for defining, solving, and simulating fully and partially observable Markov decision processes on discrete and continuous spaces.

Reduce time-to-first-execution of Julia code

Project Preferences Package

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