PUBBLICATIONS
recent publications:
S. Bordoni, A. Papaluca, P. Buttarini, A. Sopena, S. Giagu, S. Carrazza, Quantum noise modeling through Reinforcement Learning, arXiv:2408.01506 [quant-ph]
L, Colantonio, A. Cacioppo, F. Scarpati, S. Giagu, Efficient Graph Coloring with Neural Networks: A Physics-Inspired Approach for Large Graphs, arXiv:2408.01503 [cs.LG]
A. Verdone, A. Devoto, C. Sebastiani, J. Carmignani, M. D'Onofrio, S. Giagu, S. Scardapane, M. Panella, Enhancing High-Energy Particle Physics Collision Analysis through Graph Data Attribution Techniques, arXiv:2407.14859 [cs.LG]
I Ligato, G De Magistris, E Dilaghi, G Cozza, A Ciardiello, F Panzuto, S Giagu, B Annibale, C Napoli, G Esposito, Convolutional Neural Network Model for Intestinal Metaplasia Recognition in Gastric Corpus Using Endoscopic Image Patches, Diagnostics 2024, 14(13), 1376; https://doi.org/10.3390/diagnostics14131376
A Cacioppo, L Colantonio, S Bordoni, S Giagu, Quantum Diffusion Models, arXiv:2311.15444 [quant-ph] (submitted to nature quantum machine intelligence)
A Baiocchi, S Giagu, C Napoli, M Serra, P Nardelli, M Valleriani, Artificial neural networks exploiting point cloud data for fragmented solid objects classification, Mach. Learn.: Sci. Technol. 4 045025 (2023)
G Fumero, G Batignani, E Cassetta, C Ferrante, S Giagu, T Scopigno, Retrieving genuine nonlinear Raman responses in ultrafast spectroscopy via deep learning, arXiv:2309.16933 [physics.optics] (submitted to ACS Photonics)
L Maglianella, L Nicoletti, S Giagu*, C Napoli, S Scardapane, Convergent Approaches to AI Explainability for HEP Muonic Particles Pattern Recognition. Comput Softw Big Sci 7, 8 (2023). https://doi.org/10.1007/s41781-023-00102-z
A Coccaro, FA Di Bello, S Giagu, L Rambelli, N Stocchetti, Fast Neural Network Inference on FPGAs for Triggering on Long-Lived Particles at Colliders, Mach. Learn.: Sci. Technol. 4 045040, DOI 10.1088/2632-2153/ad087a, arXiv:2307.05152 [hep-ex]
S Bordoni, S. Giagu, Convolutional neural network based decoders for surface codes, Quantum Inf Process 22, 151 (2023). https://doi.org/10.1007/s11128-023-03898-2
L Arsini, B Caccia, A Ciardiello, S Giagu, C Mancini Terracciano, Nearest Neighbours Graph Variational AutoEncoder, Algorithms 2023, 16(3), 143; https://doi.org/10.3390/a16030143
S Bordoni, D Stanev, T Santantonio, S Giagu, Long-Lived Particles Anomaly Detection with Parametrized Quantum Circuits, Particles 2023, 6(1), 297-311; https://doi.org/10.3390/particles6010016
S Giagu, L Torresi, M Di Filippo, Tau Lepton Identification With Graph Neural Networks at Future Electron–Positron Colliders, Front. Phys., 19 July 2022, Volume 10 - 2022, https://doi.org/10.3389/fphy.2022.909205
S Francescato, S Giagu, F Riti, G Russo, L Sabetta, F Tortonesi, Model compression and simplification pipelines for fast deep neural network inference in FPGAs in HEP, The European Physical Journal C 81 (11), 969 (2021), https://epjc.epj.org/10.1140/epjc/s10052-021-09875-2