CAQFM adds controlled quantum gates based on Pearson, Spearman, Kendall Tau, Mutual Information, and Distance Correlation measures to create richer feature maps, yielding higher accuracy than standard maps in VQC simulations on three benchmark datasets.
A Review of Quantum Neural Networks: Methods, Models, Dilemma,
2 Pith papers cite this work. Polarity classification is still indexing.
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quant-ph 2years
2026 2verdicts
UNVERDICTED 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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A Correlation Aware Quantum Feature Map for Variational Quantum Classification
CAQFM adds controlled quantum gates based on Pearson, Spearman, Kendall Tau, Mutual Information, and Distance Correlation measures to create richer feature maps, yielding higher accuracy than standard maps in VQC simulations on three benchmark datasets.
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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.