Titlebook: Computer Aided Verification; 33rd International C Alexandra Silva,K. Rustan M. Leino Conference proceedings‘‘‘‘‘‘‘‘ 2021 The Editor(s) (if

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https://doi.org/10.1007/978-3-663-05113-8the .. . first uses . to find potentially faulty network parameters (such as the .) and then performs . using . to apply small modifications to the parameters to remedy the defects. We present novel strategies to enable precise yet efficient repair such as inferring correctness specifications to act

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Walter Eversheim,Werner Fischer,Hans Seiferte several challenges. First, verifier developers must contend with the rapidly changing DNN field to support new DNN operations and property types. Second, verifier users have the burden of selecting a verifier input format to specify their problem. Due to the many input formats, this decision can g

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Situation der Materialbeschaffung,assical classifiers and applications to data analytics in quantum physics that can be implemented on the near future quantum computers. However, quantum noise is a major obstacle to the practical implementation of quantum machine learning. In this work, we define a formal framework for the robustnes

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