Verification of Non-Linear Specifications for Neural Networks

ICLR 2019 Chongli QinKrishnamurthyDvijothamBrendan O'DonoghueRudy BunelRobert StanforthSven GowalJonathan UesatoGrzegorz SwirszczPushmeet Kohli

Prior work on neural network verification has focused on specifications that are linear functions of the output of the network, e.g., invariance of the classifier output under adversarial perturbations of the input. In this paper, we extend verification algorithms to be able to certify richer properties of neural networks... (read more)

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