Advances in verification of ReLU neural networks

DOI10.1007/s10898-020-00949-1zbMath1478.68172OpenAlexW3033072407MaRDI QIDQ2046329

Ansgar Rössig, Milena R. Petkovic

Publication date: 17 August 2021

Published in: Journal of Global Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10898-020-00949-1

zbMATH Keywords

MIPReLUneural networks verification

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Specification and verification (program logics, model checking, etc.) (68Q60)

Uses Software

• SCIP
• Reluplex
• AI2
• RecurJac

Cites Work

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• Three enhancements for optimization-based bound tightening
• Deep neural networks and mixed integer linear optimization
• Reluplex: an efficient SMT solver for verifying deep neural networks
• Challenging SMT solvers to verify neural networks
• Optimal Approximation with Sparsely Connected Deep Neural Networks
• Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks
• Strong mixed-integer programming formulations for trained neural networks

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