Classical data noise significantly amplifies the accuracy drop caused by quantum decoherence in a variational quantum classifier.
Explaining and harnessing adversarial examples
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A survey that categorizes uncertainty quantification approaches for graphical models into representation and handling dimensions to identify challenges and opportunities.
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A Systematic Study of Noise Effects in Hybrid Quantum-Classical Machine Learning
Classical data noise significantly amplifies the accuracy drop caused by quantum decoherence in a variational quantum classifier.
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Uncertainty Quantification on Graph Learning: A Survey
A survey that categorizes uncertainty quantification approaches for graphical models into representation and handling dimensions to identify challenges and opportunities.