Reverse Faà di Bruno's Formula for Cartesian Reverse Differential Categories

Reverse differentiation is an essential operation for automatic differentiation.Cartesian reverse differential categories axiomatize reverse differentiation in a categorical framework, where one of the primary axioms is the reverse chain rule, which is the formula that expresses the reverse derivative of a composition.Here, we present the reverse differential analogue of Fa di Bruno's Formula, which gives a higher-order reverse chain rule in a Cartesian reverse differential category.To properly do so, we also define partial reverse derivatives and higher-order reverse derivatives in a Cartesian reverse differential category.

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Publication Details

Journal
Electronic Proceedings in Theoretical Computer Science
Published
2025-09-22
DOI
https://doi.org/10.4204/eptcs.429.6
Primary Topic
Functional Equations Stability Results
Type
article
Field-Weighted Citation Impact
0.00

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article

Reverse Faà di Bruno's Formula for Cartesian Reverse Differential Categories

Jean-Simon Pacaud Lemay, Aaron Biggin
Electronic Proceedings in Theoretical Computer Science
Functional Equations Stability Results
article

Reverse Faà di Bruno's Formula for Cartesian Reverse Differential Categories

Jean-Simon Pacaud Lemay, Aaron Biggin
article en

Abstract

Reverse differentiation is an essential operation for automatic differentiation.Cartesian reverse differential categories axiomatize reverse differentiation in a categorical framework, where one of the primary axioms is the reverse chain rule, which is the formula that expresses the reverse derivative of a composition.Here, we present the reverse differential analogue of Fa di Bruno's Formula, which gives a higher-order reverse chain rule in a Cartesian reverse differential category.To properly do so, we also define partial reverse derivatives and higher-order reverse derivatives in a Cartesian reverse differential category.

Electronic Proceedings in Theoretical Computer ScienceVol. 429
Macquarie University (AU)
Macquarie University, Air Force Office of Scientific Research
Openalex Percentile: Top 63%
Functional Equations Stability Results
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