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Scalable Quantitative Verification For Deep Neural Networks

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE), pp.312-323, (2021)

Cited: 10|Views83
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Abstract

Despite the functional success of deep neural networks (DNNs), their trustworthiness remains a crucial open challenge. To address this challenge, both testing and verification techniques have been proposed. But these existing techniques provide either scalability to large networks or formal guarantees, not both. In this paper, we propose ...More

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