Zobrazeno 1 - 10
of 503
pro vyhledávání: '"Rigazzi A"'
Publikováno v:
Meccanica, 2024
Combining machine learning (ML) with computational fluid dynamics (CFD) opens many possibilities for improving simulations of technical and natural systems. However, CFD+ML algorithms require exchange of data, synchronization, and calculation on hete
Externí odkaz:
http://arxiv.org/abs/2402.16196
Autor:
Balin, Riccardo, Simini, Filippo, Simpson, Cooper, Shao, Andrew, Rigazzi, Alessandro, Ellis, Matthew, Becker, Stephen, Doostan, Alireza, Evans, John A., Jansen, Kenneth E.
Recent years have seen many successful applications of machine learning (ML) to facilitate fluid dynamic computations. As simulations grow, generating new training datasets for traditional offline learning creates I/O and storage bottlenecks. Additio
Externí odkaz:
http://arxiv.org/abs/2306.12900
Publikováno v:
Il Foro Italiano, 1905 Jan 01. 30, 169/170-173/174.
Externí odkaz:
https://www.jstor.org/stable/23107942
Publikováno v:
Il Foro Italiano, 1938 Jan 01. 63, 135/136-135/136.
Externí odkaz:
https://www.jstor.org/stable/23132141
Publikováno v:
Il Foro Italiano, 1938 Jan 01. 63, 97/98-99/100.
Externí odkaz:
https://www.jstor.org/stable/23136121
Publikováno v:
Il Foro Italiano, 1938 Jan 01. 63, 599/600-599/600.
Externí odkaz:
https://www.jstor.org/stable/23141620
Publikováno v:
Il Foro Italiano, 1920 Jan 01. 45, 345/346-347/348.
Externí odkaz:
https://www.jstor.org/stable/23119660
Autor:
Bulmer, Jacob F. F., Bell, Bryn A., Chadwick, Rachel S., Jones, Alex E., Moise, Diana, Rigazzi, Alessandro, Thorbecke, Jan, Haus, Utz-Uwe, Van Vaerenbergh, Thomas, Patel, Raj B., Walmsley, Ian A., Laing, Anthony
Publikováno v:
Sci. Adv. 8, eabl9236 (2022)
Identifying the boundary beyond which quantum machines provide a computational advantage over their classical counterparts is a crucial step in charting their usefulness. Gaussian Boson Sampling (GBS), in which photons are measured from a highly enta
Externí odkaz:
http://arxiv.org/abs/2108.01622
Autor:
Partee, Sam, Ellis, Matthew, Rigazzi, Alessandro, Bachman, Scott, Marques, Gustavo, Shao, Andrew, Robbins, Benjamin
We demonstrate the first climate-scale, numerical ocean simulations improved through distributed, online inference of Deep Neural Networks (DNN) using SmartSim. SmartSim is a library dedicated to enabling online analysis and Machine Learning (ML) for
Externí odkaz:
http://arxiv.org/abs/2104.09355
Autor:
Camargo, Juan Sebastian, Coronado, Estefanía, Ramirez, Wilson, Camps, Daniel, Deutsch, Sergi Sánchez, Pérez-Romero, Jordi, Antonopoulos, Angelos, Trullols-Cruces, Oscar, Gonzalez-Diaz, Sergio, Otura, Borja, Rigazzi, Giovanni
Publikováno v:
In Computer Networks November 2023 236