7 citations · 13 across the 7 of their papers we have counts for
5 papers · 1 filter
QSentry: Backdoor Detection for Quantum Neural Networks via Measurement Clustering
Shuolei Wang, Zimeng Xiao, Jinjing Shi +3
Quantum neural networks (QNNs) are an important model for implementing quantum machine learning (QML), while they demonstrate a high degree of vulnerability to backdoor attacks sim…
QAMA: Scalable Quantum Annealing Multi-Head Attention Operator for Deep Learning
Peng Du, Jinjing Shi, Wenxuan Wang +3
Attention mechanisms underpin modern deep learning, while the quadratic time and space complexity limit scalability for long sequences. To address this, Quantum Annealing Multi-Hea…
QGHNN: A quantum graph Hamiltonian neural network
Wenxuan Wang
Representing and learning from graphs is essential for developing effective machine learning models tailored to non-Euclidean data. While Graph Neural Networks (GNNs) strive to add…
Personalized Quantum Federated Learning for Privacy Image Classification
Jinjing Shi, Tian Chen, Shichao Zhang +1
Quantum federated learning has brought about the improvement of privacy image classification, while the lack of personality of the client model may contribute to the suboptimal of…
GQHAN: A Grover-inspired Quantum Hard Attention Network
Ren-Xin Zhao, Jinjing Shi, Xuelong Li
Numerous current Quantum Machine Learning (QML) models exhibit an inadequacy in discerning the significance of quantum data, resulting in diminished efficacy when handling extensiv…