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- FiniteDiff.jl Public
Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support
- ChainRulesCore.jl Public
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.
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- ChainRules.jl Public
forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs
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- SparseDiffTools.jl Public
Fast jacobian computation through sparsity exploitation and matrix coloring
- PolyesterForwardDiff.jl Public
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