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Provably correct, asymptotically efficient, higher-order reverse-mode automatic differentiation

Faustyna Krawiec, Simon Peyton Jones, Neel Krishnaswami, T. M. R. Ellis, Richard A. Eisenberg, Andrew Fitzgibbon

2022Proceedings of the ACM on Programming Languages28 citationsDOIOpen Access PDF

Abstract

In this paper, we give a simple and efficient implementation of reverse-mode automatic differentiation, which both extends easily to higher-order functions, and has run time and memory consumption linear in the run time of the original program. In addition to a formal description of the translation, we also describe an implementation of this algorithm, and prove its correctness by means of a logical relations argument.

Topics & Concepts

CorrectnessComputer scienceAutomatic differentiationSimple (philosophy)Argument (complex analysis)Mode (computer interface)Translation (biology)AlgorithmConstruct (python library)Order (exchange)Theoretical computer scienceProgramming languagePhilosophyBiochemistryComputationChemistryFinanceOperating systemEpistemologyMessenger RNAEconomicsGeneAdvanced Control Systems OptimizationFormal Methods in VerificationNumerical Methods and Algorithms
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