Zobrazeno 1 - 10
of 11 998
pro vyhledávání: '"A. Lio"'
Autor:
Giovanni Vento, Angela Paladini, C. Aurilia, S. Alkan Ozdemir, V. P. Carnielli, F. Cools, S. Costa, F. Cota, C. Dani, P. G. Davis, S. Fattore, C. Fè, N. Finer, F. P. Fusco, C. Gizzi, E. Herting, M. Jian, A. Lio, G. Lista, F. Mosca, S. Nobile, A. Perri, S. Picone, J. J. Pillow, G. Polglase, T. Pasciuto, R. Pastorino, M. Tana, D. Tingay, C. Tirone, A. H. van Kaam, M. L. Ventura, A. Aceti, M. Agosti, G. Alighieri, G. Ancora, V. Angileri, G. Ausanio, S. Aversa, E. Balestri, E. Baraldi, M. C. Barbini, C. Barone, R. Beghini, C. Bellan, A. Berardi, I. Bernardo, P. Betta, M. Binotti, B. Bizzarri, G. Borgarello, S. Borgione, A. Borrelli, R. Bottino, G. Bracaglia, I. Bresesti, I. Burattini, C. Cacace, F. Calzolari, M. F. Campagnoli, L. Capasso, M. Capozza, M. G. Capretti, J. Caravetta, C. Carbonara, V. Cardilli, M. Carta, F. Castoldi, A. Castronovo, E. Cavalleri, F. Cavigioli, S. Cecchi, V. Chierici, C. Cimino, F. Cocca, C. Cocca, P. Cogo, M. Coma, V. Comito, V. Condò, C. Consigli, R. Conti, M. Corradi, G. Corsello, L. T. Corvaglia, A. Costa, A. Coscia, F. Cresi, F. Crispino, P. D’Amico, L. De Cosmo, C. De Maio, G. Del Campo, S. Di Credico, S. Di Fabio, P. Di Nicola, A. Di Paolo, S. Di Valerio, A. Distilo, V. Duca, A. Falcone, R. Falsaperla, V. A. Fasolato, V. Fatuzzo, F. Favini, M. P. Ferrarello, S. Ferrari, F. Fiori Nastro, C. A. Forcellini, A. Fracchiolla, A. Gabriele, F. Galdo, F. Gallini, A. Gangemi, G. Gargano, D. Gazzolo, M. P. Gentile, S. Ghirardello, F. Giardina, L. Giordano, E. Gitto, M. Giuffrè, L. Grappone, F. Grasso, I. Greco, A. Grison, R. Guglielmino, I. Guidotti, I. Guzzo, N. La Forgia, S. La Placa, G. La Torre, P. Lago, L. Lanciotti, A. Lavizzari, F. Leo, V. Leonardi, D. Lestingi, J. Li, P. Liberatore, D. Lodin, R. Lubrano, M. Lucente, S. Luciani, D. Luvarà, G. Maffei, A. Maggio, L. Maggio, K. Maiolo, L. Malaigia, G. Mangili, A. Manna, E. Maranella, A. Marciano, P. Marcozzi, M. Marletta, L. Marseglia, D. Martinelli, S. Martinelli, S. Massari, L. Massenzi, F. Matina, L. Mattia, G. Mescoli, I. V. Migliore, D. Minghetti, I. Mondello, S. Montano, G. Morandi, N. Mores, S. Morreale, I. Morselli, M. Motta, M. Napolitano, D. Nardo, A. Nicolardi, S. Nider, G. Nigro, M. Nuccio, L. Orfeo, C. Ottaviano, P. Paganin, S. Palamides, S. Palatta, P. Paolillo, M. G. Pappalardo, E. Pasta, L. Patti, G. Paviotti, R. Perniola, G. Perotti, S. Perrone, F. Petrillo, M. S. Piazza, A. Piccirillo, M. Pierro, E. Piga, G. A. Pingitore, S. Pisu, C. Pittini, F. Pontiggia, G. Pontrelli, A. Primavera, A. Proto, L. Quartulli, F. Raimondi, L. Ramenghi, M. Rapsomaniki, A. Ricotti, C. Rigotti, M. Rinaldi, F. M. Risso, E. Roma, E. Romanini, V. Romano, E. Rosati, V. Rosella, I. Rulli, V. Salvo, C. Sanfilippo, A. Sannia, A. Saporito, A. Sauna, E. Scapillati, F. Schettini, A. Scorrano, S. Semeria Mantelli, V. Sepporta, P. Sindico, A. Solinas, E. Sorrentino, E. Spaggiari, A. Staffler, M. Stella, D. Termini, G. Terrin, A. Testa, G. Tina, M. Tirantello, B. Tomasini, F. Tormena, L. Travan, D. Trevisanuto, G. Tuling, V. Tulino, L. Valenzano, S. Vedovato, S. Vendramin, P. E. Villani, S. Viola, V. Viola, G. Vitaliti, M. Vitaliti, P. Wanker, Y. Yang, S. Zanetta, E. Zannin
Publikováno v:
Trials, Vol 25, Iss 1, Pp 1-18 (2024)
Abstract Background Surfactant is a well-established therapy for preterm neonates affected by respiratory distress syndrome (RDS). The goals of different methods of surfactant administration are to reduce the duration of mechanical ventilation and th
Externí odkaz:
https://doaj.org/article/6d25d8972ebb4da7aceccdf7e22b30d8
Autor:
Duta, Iulia, Liò, Pietro
The importance of higher-order relations is widely recognized in a large number of real-world systems. However, annotating them is a tedious and sometimes impossible task. Consequently, current approaches for data modelling either ignore the higher-o
Externí odkaz:
http://arxiv.org/abs/2410.03208
Autor:
Singh, Vikash, Khanzadeh, Matthew, Davis, Vincent, Rush, Harrison, Rossi, Emanuele, Shrader, Jesse, Lio, Pietro
We present Bayesian Binary Search (BBS), a novel probabilistic variant of the classical binary search/bisection algorithm. BBS leverages machine learning/statistical techniques to estimate the probability density of the search space and modifies the
Externí odkaz:
http://arxiv.org/abs/2410.01771
Heterogeneous graphs, with nodes and edges of different types, are commonly used to model relational structures in many real-world applications. Standard Graph Neural Networks (GNNs) struggle to process heterogeneous data due to oversmoothing. Instea
Externí odkaz:
http://arxiv.org/abs/2409.08036
Neural Algorithmic Reasoning (NAR) aims to optimize classical algorithms. However, canonical implementations of NAR train neural networks to return only a single solution, even when there are multiple correct solutions to a problem, such as single-so
Externí odkaz:
http://arxiv.org/abs/2409.06953
Autor:
Wang, Chong, Li, Mengyao, He, Junjun, Wang, Zhongruo, Darzi, Erfan, Chen, Zan, Ye, Jin, Li, Tianbin, Su, Yanzhou, Ke, Jing, Qu, Kaili, Li, Shuxin, Yu, Yi, Liò, Pietro, Wang, Tianyun, Wang, Yu Guang, Shen, Yiqing
Recent breakthroughs in large language models (LLMs) offer unprecedented natural language understanding and generation capabilities. However, existing surveys on LLMs in biomedicine often focus on specific applications or model architectures, lacking
Externí odkaz:
http://arxiv.org/abs/2409.00133
Autor:
Bergna, Richard, Calvo-Ordoñez, Sergio, Opolka, Felix L., Liò, Pietro, Hernandez-Lobato, Jose Miguel
We address the problem of learning uncertainty-aware representations for graph-structured data. While Graph Neural Ordinary Differential Equations (GNODE) are effective in learning node representations, they fail to quantify uncertainty. To address t
Externí odkaz:
http://arxiv.org/abs/2408.16115
Autor:
Shen, Yiqing, Chen, Zan, Mamalakis, Michail, Liu, Yungeng, Li, Tianbin, Su, Yanzhou, He, Junjun, Liò, Pietro, Wang, Yu Guang
The structural similarities between protein sequences and natural languages have led to parallel advancements in deep learning across both domains. While large language models (LLMs) have achieved much progress in the domain of natural language proce
Externí odkaz:
http://arxiv.org/abs/2408.15299
Autor:
Cao, Panfeng, Lio, Pietro
Sequential recommendation is a task to capture hidden user preferences from historical user item interaction data and recommend next items for the user. Significant progress has been made in this domain by leveraging classification based learning met
Externí odkaz:
http://arxiv.org/abs/2407.21191
Autor:
Caralt, Ferran Hernandez, Gil, Guillermo Bernárdez, Duta, Iulia, Liò, Pietro, Cot, Eduard Alarcón
Sheaf Neural Networks (SNNs) naturally extend Graph Neural Networks (GNNs) by endowing a cellular sheaf over the graph, equipping nodes and edges with vector spaces and defining linear mappings between them. While the attached geometric structure has
Externí odkaz:
http://arxiv.org/abs/2407.20597