HQ-LP-FNO replaces part of the spectral channel mixing in a 3D FNO with a mode-shared VQC, reducing parameters by 15.6% and phase-fraction MAE by 26% on laser-processing surrogates while remaining stable under calibrated noise.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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quant-ph 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Quantum feature maps from trained VQCs boost land-cover classification performance when reused in classical kernel-based frameworks, though linear-readout VQCs fail to surpass RBF-SVM baselines on EuroSAT-MS.
citing papers explorer
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Hybrid Fourier Neural Operator for Surrogate Modeling of Laser Processing with a Quantum-Circuit Mixer
HQ-LP-FNO replaces part of the spectral channel mixing in a 3D FNO with a mode-shared VQC, reducing parameters by 15.6% and phase-fraction MAE by 26% on laser-processing surrogates while remaining stable under calibrated noise.
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Parameterized Quantum Circuits as Feature Maps: Representation Quality and Readout Effects in Multispectral Land-Cover Classification
Quantum feature maps from trained VQCs boost land-cover classification performance when reused in classical kernel-based frameworks, though linear-readout VQCs fail to surpass RBF-SVM baselines on EuroSAT-MS.