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Found 2 papers, 1 papers with code
Optimizing Quantum Convolutional Neural Network Architectures for Arbitrary Data Dimension
Quantum convolutional neural networks (QCNNs) represent a promising approach in quantum machine learning, paving new directions for both quantum and classical data analysis.
Variational Quantum Approximate Support Vector Machine with Inference Transfer
A kernel-based quantum classifier is the most practical and influential quantum machine learning technique for the hyper-linear classification of complex data.
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