5 papers · 1 filter
BVQC: A Backdoor-style Watermarking Scheme for Variational Quantum Circuits
Cheng Chu, Lei Jiang, Fan Chen
Variational Quantum Circuits (VQCs) have emerged as a powerful quantum computing paradigm, demonstrating a scaling advantage for problems intractable for classical computation. As…
LSTM-QGAN: Scalable NISQ Generative Adversarial Network
Cheng Chu, Aishwarya Hastak, Fan Chen
Current quantum generative adversarial networks (QGANs) still struggle with practical-sized data. First, many QGANs use principal component analysis (PCA) for dimension reduction,…
QuantumLeak: Stealing Quantum Neural Networks from Cloud-based NISQ Machines
Zhenxiao Fu, Min Yang, Cheng Chu +3
Variational quantum circuits (VQCs) have become a powerful tool for implementing Quantum Neural Networks (QNNs), addressing a wide range of complex problems. Well-trained VQCs serv…
CryptoQFL: Quantum Federated Learning on Encrypted Data
Cheng Chu, Lei Jiang, Fan Chen
Recent advancements in Quantum Neural Networks (QNNs) have demonstrated theoretical and experimental performance superior to their classical counterparts in a wide range of applica…
QDoor: Exploiting Approximate Synthesis for Backdoor Attacks in Quantum Neural Networks
Cheng Chu, Fan Chen, Philip Richerme +1
Quantum neural networks (QNNs) succeed in object recognition, natural language processing, and financial analysis. To maximize the accuracy of a QNN on a Noisy Intermediate Scale Q…