ImplicitDifferentiation.jl: differentiating implicit functions
Mohamed Tarek, Guillaume Dalle
We present a Julia package for differentiating through functions that are defined implicitly. It can be used to compute derivatives for a wide array of "black box" procedures, from optimization algorithms to fixed point iterations or systems of nonlinear equations.
Since it mostly relies on defining custom chain rules, our code is lightweight and integrates nicely with Julia's automatic differentiation and machine learning ecosystem.
