Q-SafeML applies quantum distance metrics, such as trace distance and fidelity, to compare correct and incorrect predictions of quantum classifiers, offering a way to flag unsafe or unreliable QML behavior.
In: Model-Based Safety and Assessment: 8th International Symposium, IMBSA 2022, Munich, Germany, September 5–7
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Q-SafeML: Safety Assessment of Quantum Machine Learning via Quantum Distance Metrics
Q-SafeML applies quantum distance metrics, such as trace distance and fidelity, to compare correct and incorrect predictions of quantum classifiers, offering a way to flag unsafe or unreliable QML behavior.