JamesYang007 / FastAD

FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
MIT License
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Jacobian #101

Open nourgaliev opened 3 years ago

nourgaliev commented 3 years ago

Can we get any example when we have an array of functions, rather than a single one. This is quite a common case, when we need to compute Jacobian. I think I have some idea how to do that, but I am not sure this would be efficient.

sofusmo commented 4 months ago

Yeah - this seems to be a weak point of this library. Doing a Jacobian for complex calculations is one place where an effort like Adept I would expect to clearly be faster, as the adjoint evaluation is a separate final step.

It doesn't seem to be easy to change. @JamesYang007 do you have suggestions for how to improve this?