A neural network is trained to predict parameters of a fixed quantum circuit, enabling high-fidelity quantum state preparation from classical data in one inference step with up to 0.992 fidelity on unseen MNIST and Fashion-MNIST images.
Classification of the Fashion-MNIST dataset on a quan- tum computer,
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Shot-based quantum encoding embeds data as a classical probability mixture over basis states, making the quantum layer a linear map on probabilities—structurally a classical MLP.
citing papers explorer
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Quantum State Preparation via Neural Network Encoding in Quantum Machine Learning
A neural network is trained to predict parameters of a fixed quantum circuit, enabling high-fidelity quantum state preparation from classical data in one inference step with up to 0.992 fidelity on unseen MNIST and Fashion-MNIST images.
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Shot-based quantum encoding: a data-loading paradigm for quantum neural networks
Shot-based quantum encoding embeds data as a classical probability mixture over basis states, making the quantum layer a linear map on probabilities—structurally a classical MLP.