Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Vincent Ginis"'
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-11 (2023)
Resonators are key components in optics. In this work, the authors introduce a class of optical resonators with distinctly different properties from conventional resonators, allowing fundamental design trade-offs to be circumvented.
Externí odkaz:
https://doaj.org/article/d40783faa7254289b3dc6666105c0ebf
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-9 (2022)
Abstract Expected values are the metric most often used to judge human decision-making; when humans make decisions that do not optimize expected values, these decisions are considered irrational. However, while convenient, expected values do not nece
Externí odkaz:
https://doaj.org/article/ee08663b322147e089d8f352599f7189
Publikováno v:
IEEE Access, Vol 9, Pp 52079-52088 (2021)
Recent research has indicated considerable potential for millimeter-waves in copper access, with data-rate estimations up to 1 Terabit per second for a reach of 100 m. This line of research exploits millimeter-waves and their corresponding higher-ord
Externí odkaz:
https://doaj.org/article/6e05f5f588b942809d3e2086d776b290
Autor:
Floriano Tori, Vincent Ginis
Publikováno v:
Physical Review Research, Vol 4, Iss 4, p 043090 (2022)
The ability to solve differential equations represents a key step in the modeling and understanding of complex systems. There exist several analytical and numerical methods for solving differential equations, each with their own advantages and limita
Externí odkaz:
https://doaj.org/article/51f51aa666694f7a9f56c8b1aaaf553d
Autor:
Joeri Lenaerts, Vincent Ginis
Publikováno v:
Physical Review Research, Vol 4, Iss 2, p 023206 (2022)
When studying a physical system, it is crucial to identify the degrees of freedom that characterize that system. Recently, specific neural networks have been designed to retrieve these underlying degrees of freedom automatically. Indeed, fed with dat
Externí odkaz:
https://doaj.org/article/ef4bb4c94f014651973c58f9a5b0d9dd
Publikováno v:
Physical Review Letters. 130
Multitask learning (MTL) can improve performance on one task by sharing representations with one or more related auxiliary tasks. Usually, MTL networks are trained on a composite loss function formed by a fixed weighted combination of separate task l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bdd4cf2f3d5689c671e94b19aed0a056
https://biblio.vub.ac.be/vubir/(2de548f2-cc51-4e58-9425-159a8967e6e3).html
https://biblio.vub.ac.be/vubir/(2de548f2-cc51-4e58-9425-159a8967e6e3).html
Autor:
Vincent Ginis, Floriano Tori
The ability to solve differential equations represents a key step in the modeling and understanding of complex systems. There exist several analytical and numerical methods for solving differential equations, each with their own advantages and limita
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c98019ef955892adcbd55aa865b86c9
https://hdl.handle.net/20.500.14017/d754d3d6-b8e3-4bc6-b3f5-63b9b8b57ed9
https://hdl.handle.net/20.500.14017/d754d3d6-b8e3-4bc6-b3f5-63b9b8b57ed9
Publikováno v:
IEEE Access, Vol 9, Pp 52079-52088 (2021)
Recent research has indicated considerable potential for millimeter-waves in copper access, with data-rate estimations up to 1 Terabit per second for a reach of 100 m. This line of research exploits millimeter-waves and their corresponding higher-ord
Publikováno v:
Nanophotonics, Vol 10, Iss 1, Pp 385-392 (2020)
Machine learning offers the potential to revolutionize the inverse design of complex nanophotonic components. Here, we propose a novel variant of this formalism specifically suited for the design of resonant nanophotonic components. Typically, the fi