5 papers
QuaRK: A Quantum Reservoir Kernel for Time Series Learning
Abdallah Aaraba, Soumaya Cherkaoui, Ola Ahmad +1
Quantum reservoir computing offers a promising route for time series learning by modelling sequential data via rich quantum dynamics while the only training required happens at the…
Quantum Gated Recurrent GAN with Gaussian Uncertainty for Network Anomaly Detection
Wajdi Hammami, Soumaya Cherkaoui, Jean-Frederic Laprade +2
Anomaly detection in time-series data is a critical challenge with significant implications for network security. Recent quantum machine learning approaches, such as quantum kernel…
Multivariate Time Series Forecasting with Gate-Based Quantum Reservoir Computing on NISQ Hardware
Wissal Hamhoum, Soumaya Cherkaoui, Jean-Frederic Laprade +3
Quantum reservoir computing (QRC) offers a hardware-friendly approach to temporal learning, yet most studies target univariate signals and overlook near-term hardware constraints.…
Enhancing Network Anomaly Detection with Quantum GANs and Successive Data Injection for Multivariate Time Series
Wajdi Hammami, Soumaya Cherkaoui, Shengrui Wang
Quantum computing may offer new approaches for advancing machine learning, including in complex tasks such as anomaly detection in network traffic. In this paper, we introduce a qu…
LatentQGAN: A Hybrid QGAN with Classical Convolutional Autoencoder
Alexis Vieloszynski, Soumaya Cherkaoui, Ola Ahmad +4
Quantum machine learning consists in taking advantage of quantum computations to generate classical data. A potential application of quantum machine learning is to harness the powe…