Forward Mode Automatic Differentiation for Julia

Reverse Mode Automatic Differentiation for Julia

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

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

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

Fast jacobian computation through sparsity exploitation and matrix coloring

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

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

Julia package for representing dual numbers and for performing dual algebra

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 implementation of HyperDualNumbers

A simple shared suite of common derivative definitions

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.

Utilities for testing custom forward- and reverse-mode AD primatives.