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Towards quantum enhanced adversarial robustness in machine learning - Nature Machine Intelligence

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Towards quantum enhanced adversarial robustness in machine learning - Nature Machine Intelligence

Machine learning algorithms are powerful tools for data-driven tasks such as image classification and feature detection. However, their vulnerability to adversarial examples—input samples manipulated to fool the algorithm—remains a serious challenge. The integration of machine learning with quantum computing has the potential to yield tools offering not only better accuracy and computational efficiency, but also superior robustness against adversarial attacks.

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Towards quantum enhanced adversarial robustness in machine learning - Nature Machine Intelligence

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Towards quantum enhanced adversarial robustness in machine learning - Nature Machine Intelligence

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