18 citations · 30 across the 4 of their papers we have counts for
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quant-ph2024★ 12 cited
Optimizing Quantum Convolutional Neural Network Architectures for Arbitrary Data Dimension
Changwon Lee, Israel F. Araujo, Dongha Kim +4
Quantum convolutional neural networks (QCNNs) represent a promising approach in quantum machine learning, paving new directions for both quantum and classical data analysis. This a…
quant-ph2024
Quantum-inspired classification via efficient simulation of Helstrom measurement
Wooseop Hwang, Daniel K. Park, Israel F. Araujo +1
The Helstrom measurement (HM) is known to be the optimal strategy for distinguishing non-orthogonal quantum states with minimum error. Previously, a binary classifier based on clas…