6 papers
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…
HDM: Hybrid Diffusion Model for Unified Image Anomaly Detection
Zekang Weng, Jinjin Shi, Jinwei Wang +1
Image anomaly detection plays a vital role in applications such as industrial quality inspection and medical imaging, where it directly contributes to improving product quality and…
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…
QuanTest: Entanglement-Guided Testing of Quantum Neural Network Systems
Jinjing Shi, Zimeng Xiao, Heyuan Shi +2
Quantum Neural Network (QNN) combines the Deep Learning (DL) principle with the fundamental theory of quantum mechanics to achieve machine learning tasks with quantum acceleration.…