The Hamming quantum kernel, built from full measurement statistics of the same quantum circuits used for fidelity kernels, outperforms the fidelity kernel at 15+ qubits and the classical Gaussian kernel on synthetic quantum data up to 27 qubits.
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quant-ph 2years
2026 2representative citing papers
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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Support Vector Machine with a Scalable Quantum Kernel
The Hamming quantum kernel, built from full measurement statistics of the same quantum circuits used for fidelity kernels, outperforms the fidelity kernel at 15+ qubits and the classical Gaussian kernel on synthetic quantum data up to 27 qubits.
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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.