Attention Mechanism for Quantum Neural Networks

🏷️ KOLOKIUM FISIKA KUANTUM 12-09-2024
“Attention Mechanism for Quantum Neural Networks”
🔖 PEMBICARA:
Gekko Patria Budiutama, Ph. D
Researcher @ University of Tokyo, Quemix Inc.
🗒️ KAPAN?
12 September 2024 (Kamis)
10.30-12.00 WIB
🏡 DI MANA?
Zoom Meeting BRIN Quantum:
bit.ly/kolokiu...
Meeting ID: 927 3437 3246
Passcode: quantum
📚 ABSTRACT:
Quantum neural networks (QNNs) have gathered attention as one promising approach for quantum machine learning. Reduction in the cost of training and improvement in performance are required for the practical implementation of these models. In this study, we propose a channel attention mechanism for QNNs and show the effectiveness of this approach for quantum phase classification problems using quantum convolutional neural networks (QCNNs). Our attention mechanism creates multiple channels of output state based on the measurement of quantum bits. This simple approach improves the performance of QCNNs and outperforms a conventional approach using feed-forward neural networks as the additional postprocessing.
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