Merged amplitude encoding reduces circuit executions in CCQKAN by a factor of n with 1-2 extra qubits and preserves trainability in numerical tests on networks and MNIST classification.
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2 Pith papers cite this work. Polarity classification is still indexing.
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quant-ph 2years
2026 2representative citing papers
Quantum kernel ridge regression shows double descent in test risk, with the interpolation peak suppressible by regularization, via random matrix theory asymptotics in the high-dimensional limit.
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Merged amplitude encoding for Chebyshev quantum Kolmogorov--Arnold networks: trading qubits for circuit executions
Merged amplitude encoding reduces circuit executions in CCQKAN by a factor of n with 1-2 extra qubits and preserves trainability in numerical tests on networks and MNIST classification.
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Double Descent in Quantum Kernel Ridge Regression
Quantum kernel ridge regression shows double descent in test risk, with the interpolation peak suppressible by regularization, via random matrix theory asymptotics in the high-dimensional limit.