activity
20242026
collaborators
Showing quant-phShow all

5 papers · 1 filter

quant-ph2026

Quantum Circuit-Based Learning Models: Bridging Quantum Computing and Machine Learning

Fan Fan, Yilei Shi, Mihai Datcu +5

Machine Learning (ML) has been widely applied across numerous domains due to its ability to automatically identify informative patterns from data for various tasks. The availabilit…

quant-ph2025

Quantum Latent Diffusion Models

Francesca De Falco, Andrea Ceschini, Alessandro Sebastianelli +2

The introduction of quantum concepts is increasingly making its way into generative machine learning models. However, while there are various implementations of quantum Generative…

quant-ph2024

From Graphs to Qubits: A Critical Review of Quantum Graph Neural Networks

Andrea Ceschini, Francesco Mauro, Francesca De Falco +7

Quantum Graph Neural Networks (QGNNs) represent a novel fusion of quantum computing and Graph Neural Networks (GNNs), aimed at overcoming the computational and scalability challeng…

quant-ph2024

In Search of Quantum Advantage: Estimating the Number of Shots in Quantum Kernel Methods

Artur Miroszewski, Marco Fellous Asiani, Jakub Mielczarek +2

Quantum Machine Learning (QML) has gathered significant attention through approaches like Quantum Kernel Machines. While these methods hold considerable promise, their quantum natu…

quant-ph2024

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

Su Yeon Chang, Supanut Thanasilp, Bertrand Le Saux +2

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 images…