Special mathematical functions 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.

Reduce time-to-first-execution of Julia code

Lazy code loading for Julia

Julia package for lazily representing matrices filled with a single entry

Compatibility across Julia versions

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

Project Preferences Package

Parameterise all the things

Extensions for Julia's docsystem.

Uniform Interface for positive definite matrices of various structures

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Julia-based implementation of ellipsis array indexing notation `..`

SparseArrays.jl is a Julia stdlib

A simple shared suite of common derivative definitions

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

Optimisers.jl defines many standard optimisers and utilities for learning loops.

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

Static types useful for dispatch and generated functions.

Interface for function inversion in Julia

Under some conditions you may need this function

Defines additional irrationals

Train and sample Restricted Boltzmann machines in Julia

Interface designs for enforcing static computations in array functions with Julia

Interface for transformation functions in Julia

Fixing the world one invalidator at a time.