2 papers
cs.LG2026
Quantifying Gate Contribution in Quantum Feature Maps for Scalable Circuit Optimization
F. RodrÃguez-DÃaz, D. Gutiérrez-Avilés, A. Troncoso +1
Quantum machine learning offers promising advantages for classification tasks, but noise, decoherence, and connectivity constraints in current devices continue to limit the efficie…
quant-ph2026
Hybrid Classical-Quantum Transfer Learning with Noisy Quantum Circuits
D. MartÃn-Pérez, F. RodrÃguez-DÃaz, D. Gutiérrez-Avilés +2
Quantum transfer learning combines pretrained classical deep learning models with quantum circuits to reuse expressive feature representations while limiting the number of trainabl…