Quantum Gaussian processes are defined via unitary quantum stochastic processes and proven scalable for matchgate evolutions, enabling regression, classification, and Bayesian optimization on quantum data.
Instead, empirical Bayes estimates the prior probability distribution from the data
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Provable and scalable quantum Gaussian processes for quantum learning
Quantum Gaussian processes are defined via unitary quantum stochastic processes and proven scalable for matchgate evolutions, enabling regression, classification, and Bayesian optimization on quantum data.