Neural nets via forward state transformation and backward loss transformation

DOI10.1016/J.ENTCS.2019.09.009OpenAlexW2995513139WikidataQ113317354 ScholiaQ113317354MaRDI QIDQ2133171

David Sprunger, Bart Jacobs

Publication date: 29 April 2022

Full work available at URL: https://arxiv.org/abs/1803.09356

zbMATH Keywords

neural networkmultilayer perceptronbackpropagationloss transformationstate-and-effect triangle

Mathematics Subject Classification ID

Semantics in the theory of computing (68Q55) Mathematical aspects of software engineering (specification, verification, metrics, requirements, etc.) (68N30)

Cites Work

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• A functional perspective on machine learning via programmable induction and abduction
• From probability monads to commutative effectuses
• New Directions in Categorical Logic, for Classical, Probabilistic and Quantum Logic
• The Logical Essentials of Bayesian Reasoning
• Learning representations by back-propagating errors

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