Variational quantum models
Four detailed lessons, mathematical definitions, worked examples and limitations.
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Concept 13Parameterized quantum circuitsA variational circuit combines data embedding, trainable gates and measured observables.Concept 14Variational quantum classifierConvert expectation values into binary scores and optimize a classification loss.Concept 15Quantum neural networksQNNs are compositional trainable quantum models; architecture and readout define their hypothesis class.Concept 16Parameter-shift gradientsFor certain gates, analytic derivatives are obtained from shifted circuit evaluations.