JuliaDiff/DifferentiationInterface.jl
An interface to various automatic differentiation backends in Julia.
This tool helps computational scientists and engineers who work with Julia to calculate derivatives of complex functions. It provides a standard way to input your mathematical functions and get back precise gradients, Jacobians, or Hessians, regardless of the underlying differentiation method used. This allows users to easily switch between different automatic differentiation techniques to find the best performance for their specific problem.
298 stars.
Use this if you need to compute derivatives (like gradients or Hessians) of functions in Julia and want the flexibility to try different automatic differentiation approaches without rewriting your code.
Not ideal if you are using Enzyme.jl and encounter performance issues or errors, as a direct call to its native API might be more stable.
Stars
298
Forks
29
Language
Julia
License
MIT
Category
Last pushed
Mar 09, 2026
Commits (30d)
0
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