6 papers
Scalable Quantum Molecular Generation via GPU-Accelerated Tensor-Network Simulation
Yu-Cheng Xiao, Jen-Yu Chang, Tzu-Ling Kuo +7
We propose Scalable Quantum Molecular Generation (SQMG), a variational quantum-circuit for sampling molecular graphs using chemical priors on atoms and bonds. SQMG assigns a fixed…
MPM-QIR: Measurement-Probability Matching for Quantum Image Representation and Compression via Variational Quantum Circuit
Chong-Wei Wang, Mei Ian Sam, Tzu-Ling Kuo +2
We present MPM-QIR, a variational-quantum-circuit (VQC) framework for classical image compression and representation whose core objective is to achieve equal or better reconstructi…
Quantum Graph Attention Network: A Novel Quantum Multi-Head Attention Mechanism for Graph Learning
An Ning, Tai Yue Li, Nan Yow Chen
We propose the Quantum Graph Attention Network (QGAT), a hybrid graph neural network that integrates variational quantum circuits into the attention mechanism. At its core, QGAT em…
Quantum Adaptive Excitation Network with Variational Quantum Circuits for Channel Attention
Yu-Chao Hsu, Kuan-Cheng Chen, Tai-Yue Li +1
In this work, we introduce the Quantum Adaptive Excitation Network (QAE-Net), a hybrid quantum-classical framework designed to enhance channel attention mechanisms in Convolutional…
Quantum Kernel-Based Long Short-term Memory for Climate Time-Series Forecasting
Yu-Chao Hsu, Nan-Yow Chen, Tai-Yu Li +3
We present the Quantum Kernel-Based Long short-memory (QK-LSTM) network, which integrates quantum kernel methods into classical LSTM architectures to enhance predictive accuracy an…
Quantum Pointwise Convolution: A Flexible and Scalable Approach for Neural Network Enhancement
An Ning, Tai-Yue Li, Nan-Yow Chen
In this study, we propose a novel architecture, the Quantum Pointwise Convolution, which incorporates pointwise convolution within a quantum neural network framework. Our approach…