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.gitignore Initial commit Aug 5, 2019
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README.md

ForwardDiff2

ForwardDiff2 = ForwardDiff.jl + ChainRules.jl + Struct of arrays + DualCache

Planned features:

  • works both on GPU and CPU
  • scalar forward mode AD
  • vectorized forward mode AD
  • Dual cache
  • nested differentiation
  • hyper duals (?)
  • user-extensible scalar and tensor derivative definitions
  • in-place function
  • sparsity exploitation (color vector support)
  • complex differentiation (use ChainRules.jl)
  • plays nicely with Zygote

The ForwardDiff2 source code follows the YASGuide.

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