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arXiv:1612.02731cs.SC

Automatic Differentiation: a look through Tensor and Operational Calculus

Žiga Sajovic

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Abstract

In this paper we take a look at Automatic Differentiation through the eyes of Tensor and Operational Calculus. This work is best consumed as supplementary material for learning tensor and operational calculus by those already familiar with automatic differentiation. To that purpose, we provide a simple implementation of automatic differentiation, where the steps taken are explained in the language tensor and operational calculus.

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DOI
Subjects
cs.SCSymbolic Computation math.FAFunctional Analysis

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  1. Operational calculus on programming spaces and generalized tensor networks 1 comment

    • I spent the last few hours reading this paper. From what I understand, the paper is not about AD, but something more. AD is "efficient means to calculating derivatives", as they put it. This paper seems to be about program analysis through calculus (AD comes into play, as…

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