Training embedding quantum kernels with data re-uploading quantum neural networks

P Rodriguez-Grasa, Y Ban, M Sanz - arxiv preprint arxiv:2401.04642, 2024 - arxiv.org
Kernel methods play a crucial role in machine learning and the Embedding Quantum
Kernels (EQKs), an extension to quantum systems, have shown very promising …

The role of data-induced randomness in quantum machine learning classification tasks

B Casas, X Bonet-Monroig, A Pérez-Salinas - arxiv preprint arxiv …, 2024 - arxiv.org
Quantum machine learning (QML) has surged as a prominent area of research with the
objective to go beyond the capabilities of classical machine learning models. A critical …

Data re-uploading in Quantum Machine Learning for time series: application to traffic forecasting

N Schetakis, P Bonfini, N Alisoltani, K Blazakis… - arxiv preprint arxiv …, 2025 - arxiv.org
Accurate traffic forecasting plays a crucial role in modern Intelligent Transportation Systems
(ITS), as it enables real-time traffic flow management, reduces congestion, and improves the …

Fourier Analysis of Variational Quantum Circuits for Supervised Learning

M Wiedmann, M Periyasamy, DD Scherer - arxiv preprint arxiv …, 2024 - arxiv.org
VQC can be understood through the lens of Fourier analysis. It is already well-known that
the function space represented by any circuit architecture can be described through a …

Latent Style-based Quantum GAN for high-quality Image Generation

SY Chang, S Thanasilp, BL Saux, S Vallecorsa… - arxiv preprint arxiv …, 2024 - arxiv.org
Quantum generative modeling is among the promising candidates for achieving a practical
advantage in data analysis. Nevertheless, one key challenge is to generate large-size …

arxiv: Latent Style-based Quantum GAN for high-quality Image Generation

SY Chang, M Grossi, S Thanasilp, B Le Saux… - 2024 - cds.cern.ch
Quantum generative modeling is among the promising candidates for achieving a practical
advantage in data analysis. Nevertheless, one key challenge is to generate large-size …