Verifying feedforward neural networks for classification in Isabelle/HOL

DOI10.1007/978-3-031-27481-7_24zbMath1529.68154MaRDI QIDQ6174545

Achim D. Brucker, Amy Stell

Publication date: 17 August 2023

Published in: Formal Methods (Search for Journal in Brave)

zbMATH Keywords

verificationneural networkfeedforward networkIsabelle/HOLdeep learningclassification network

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Specification and verification (program logics, model checking, etc.) (68Q60) Formalization of mathematics in connection with theorem provers (68V20)

Cites Work

• Unnamed Item
• Eisbach: a proof method language for Isabelle
• Operating system verification---an overview
• Isabelle/HOL. A proof assistant for higher-order logic
• Safety verification of deep neural networks
• Reluplex: an efficient SMT solver for verifying deep neural networks
• Building Formal Method Tools in the Isabelle/Isar Framework
• Neural Networks and Deep Learning
• Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks
• Learning representations by back-propagating errors
• Formal specification for deep neural networks

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