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Formal Specification for Deep Neural Networks

  • Author(s): Seshia, SA;
  • Desai, A;
  • Dreossi, T;
  • Fremont, DJ;
  • Ghosh, S;
  • Kim, E;
  • Shivakumar, S;
  • Vazquez-Chanlatte, M;
  • Yue, X
  • Editor(s): Lahiri, Shuvendu K;
  • Wang, Chao
  • et al.
Abstract

The increasing use of deep neural networks in a variety of applications, including some safety-critical ones, has brought renewed interest in the topic of verification of neural networks. However, verification is most meaningful when performed with high-quality formal specifications. In this paper, we survey the landscape of formal specification for deep neural networks, and discuss the opportunities and challenges for formal methods for this domain.

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