Analyzing deep neural networks with symbolic propagation: towards higher precision and faster verification

DOI10.1007/978-3-030-32304-2_15zbMATH Open1539.68173MaRDI QIDQ6536294

Jiangchao Liu, Liqian Chen, Jian-Lin Li, Lijun Zhang, Xiaowei Huang, Peng-fei Yang

Publication date: 19 April 2024

Mathematics Subject Classification ID

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

Cites Work

• Safe bounds in linear and mixed-integer linear programming
• Safety verification of deep neural networks
• Reluplex: an efficient SMT solver for verifying deep neural networks
• Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks

Related Items (2)

\textsc{OccRob}: efficient SMT-based occlusion robustness verification of deep neural networks ⋮ \textsf{QEBVerif}: quantization error bound verification of neural networks

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