A Differential-form Pullback Programming Language for Higher-order Reverse-mode Automatic Differentiation
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Building on the observation that reverse-mode automatic differentiation (AD) – a generalisation of backpropagation – can naturally be expressed as pullbacks of differential 1-forms, we design a simple higher-order programming language with a first-class differential operator, and present a reduction strategy which exactly simulates reverse-mode AD. We justify our reduction strategy by interpreting our language in any differential λ-category that satisfies the Hahn-Banach Separation Theorem, and show that the reduction strategy precisely captures reverse-mode AD in a truly higher-order setting.
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