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- An interface to various automatic differentiation backends in Julia.
Diffractor.jl
PublicForwardDiff.jl
PublicChainRules.jl
Publicforward and reverse mode automatic differentiation primitives for Julia Base + StdLibsDualNumbers.jl
PublicSparseDiffTools.jl
PublicTaylorDiff.jl
PublicTaylor-mode automatic differentiation for higher-order derivativesjuliadiff.github.io
PublicTaylorSeries.jl
PublicTaylor polynomial expansions in one and several independent variables.FiniteDiff.jl
PublicDiffResults.jl
PublicChainRulesCore.jl
PublicAD-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.ChainRulesTestUtils.jl
PublicUtilities for testing custom AD primitives.ReverseDiff.jl
PublicFiniteDifferences.jl
PublicHigh accuracy derivatives, estimated via numerical finite differences (formerly FDM.jl)PolyesterForwardDiff.jl
PublicDocThemeIndigo.jl
PublicBlueStyle
PublicA Julia style guide that lives in a blue worldDiffRules.jl
PublicDiffTests.jl
Public- Helpers for declaring ChainRules
HyperDualNumbers.jl
PublicCapstan.jl
Public