Forward Mode Automatic Differentiation for Julia

Reverse Mode Automatic Differentiation for Julia

Forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs

A julia package for Taylor polynomial expansions in one and several independent variables.

High accuracy derivatives, estimated via numerical finite differences (formerly FDM.jl)

High accuracy derivatives, estimated via numerical finite differences (formerly FDM.jl)

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

Fast jacobian computation through sparsity exploitation and matrix coloring

It is like recipes but for AD! (Full functionality is in ChainRules.jl but this a light weight dependency just to define sensitivities for your functions in your packages)

Julia package for representing dual numbers and for performing dual algebra

A Cassette-based automatic differentiation package for the Julia language

Julia implementation of HyperDualNumbers

A simple shared suite of common derivative definitions

An abstract interface for automatic differentiation.

Utilities for testing custom AD primitives.

A package which provides an API for querying differentiation results at multiple orders simultaneously

A common suite of test functions for stressing the robustness of differentiation tools.

The Documenter Theme for the ChainRules family of prackages. But you can use it too