Search Results for author:
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.
A divide-and-conquer algorithm for quantum state preparation
Results show that we can efficiently load data in quantum devices using a divide-and-conquer strategy to exchange computational time for space.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
