Classical light training of photonic quantum reservoirs enables accurate model-free estimation of single-qubit observables and two-qubit entanglement witnesses on unseen quantum states.
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Survey summarizing performance metrics of fully connected QNNs, quantum CNNs, equivariant QNNs, quantum Hopfield networks, quantum Boltzmann machines, quantum reservoir computing, and composite networks for reinforcement, generative, and transfer learning.
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Efficient classical training of model-free quantum photonic reservoir
Classical light training of photonic quantum reservoirs enables accurate model-free estimation of single-qubit observables and two-qubit entanglement witnesses on unseen quantum states.
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Research progress on quantum neural networks and quantum machine learning
Survey summarizing performance metrics of fully connected QNNs, quantum CNNs, equivariant QNNs, quantum Hopfield networks, quantum Boltzmann machines, quantum reservoir computing, and composite networks for reinforcement, generative, and transfer learning.