Reverse-Mode Automatic Differentiation in Haskell

I've uploaded a package named rad to Hackage for handling reverse-mode automatic differentiation in Haskell.

Internally, it leverages a trick from Andy Gill's Kansas Lava to observe sharing in the tape it records for back propagation purposes, and uses type level branding to avoid confusing sensitivities.

f(x, y) = xy + sin(x)

x y

Step

Loading the Haskell figure… Values flow forward; sensitivities flow backward and add at shared inputs. Haskell source · All Haskell sources.

I've tried to keep the API relatively close to that of Barak Pearlmutter and Jeffrey Mark Siskind's fad package, but I couldn't resist making a couple of minor tweaks here and there for generality.

I still need to go through and finish up the remaining unimplemented fad combinators, figure out a nice way to build a reverse-mode AD tower, validate that I didn't screw up my recollection of basic calculus, and provide a nice API for using this approach to get local reverse mode checkpoints in an otherwise forward mode AD program, but I am quite happy with how things have progressed thus far.

[Edit: I've uploaded minor bug fixes for exp and (**)]