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Variational inference with a quantum computer
One alternative is variational inference, where a candidate probability distribution is optimized to approximate the posterior distribution over unobserved variables.
Parameterized quantum circuits as machine learning models
Hybrid quantum-classical systems make it possible to utilize existing quantum computers to their fullest extent.
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