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GQHAN: A Grover-inspired Quantum Hard Attention Network
In response to the dilemma of HAM and QML, a Grover-inspired Quantum Hard Attention Mechanism (GQHAM) consisting of a Flexible Oracle (FO) and an Adaptive Diffusion Operator (ADO) is proposed.
QKSAN: A Quantum Kernel Self-Attention Network
Self-Attention Mechanism (SAM) excels at distilling important information from the interior of data to improve the computational efficiency of models.
QSAN: A Near-term Achievable Quantum Self-Attention Network
Self-Attention Mechanism (SAM) is good at capturing the internal connections of features and greatly improves the performance of machine learning models, espeacially requiring efficient characterization and feature extraction of high-dimensional data.
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