2 papers
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…
cs.LG2024
Enhancing High-Energy Particle Physics Collision Analysis through Graph Data Attribution Techniques
A. Verdone, A. Devoto, C. Sebastiani +5
The experiments at the Large Hadron Collider at CERN generate vast amounts of complex data from high-energy particle collisions. This data presents significant challenges due to it…