Overview of results
Given a QNN \(\hat{U}({\boldsymbol{\theta }})\) with L variational parameters θ = (θ1, …, θL), we consider a supervised learning task involving N quantum data \({\{\vert {\psi }_{\alpha }\rangle \}}_{\alpha = 1}^{N}\),…
Given a QNN \(\hat{U}({\boldsymbol{\theta }})\) with L variational parameters θ = (θ1, …, θL), we consider a supervised learning task involving N quantum data \({\{\vert {\psi }_{\alpha }\rangle \}}_{\alpha = 1}^{N}\),…