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quant-ph2026★ 1 cited
Analysis of Quantum Image Representations for Supervised Classification
Marco Parigi, Mehran Khosrojerdi, Filippo Caruso +1
In the era of big data and artificial intelligence, the increasing volume of data and the demand to solve more and more complex computational challenges are two driving forces for…
quant-ph2025
Physics-inspired Generative AI models via real hardware-based noisy quantum diffusion
Marco Parigi, Stefano Martina, Francesco Aldo Venturelli +1
Quantum Diffusion Models (QDMs) are an emerging paradigm in Generative AI that aims to use quantum properties to improve the performances of their classical counterparts. However,…
quant-ph2024
Quantum-Noise-Driven Generative Diffusion Models
Marco Parigi, Stefano Martina, Filippo Caruso
Generative models realized with machine learning techniques are powerful tools to infer complex and unknown data distributions from a finite number of training samples in order to…