Cuoco, Elena - Resultados da pesquisa

Pesquisar colecções:

Ordenar por:	Display results:	Output format:

CERN Document Server	3 records found	Search took 0.56 seconds.

ESCAPE - addressing Open Science challenges / Allen, Mark G. (Strasbourg Observ.) ; Lamanna, Giovanni (Annecy, LAPP) ; Espinal, Xavier (CERN) ; Graf, Kay (Erlangen - Nuremberg U., ECAP) ; van Haarlem, Michiel (ASTRON, Dwingeloo) ; Serjeant, Stephen (Open U., England) ; Bird, Ian (Annecy, LAPP) ; Cuoco, Elena (Pisa, Scuola Normale Superiore) ; Wagh, Jayesh (Annecy, LAPP)
ESCAPE (European Science Cluster of Astronomy & Particle physics ESFRI research infrastructures) is an EU H2020 project that addresses the Open Science challenges shared by the astrophysics and and accelerator-based physics and nuclear physics ESFRI projects and landmarks. This project is embedded in the context of the European Open Science Cloud (EOSC) and involves activities to develop a prototype Data Lake and Science Platform, as well as support of an Open Source Software Repository, connection of the Virtual Observatory framework to EOSC, and engaging the public in citizen science. [...]
arXiv:2012.11534.- 2022 - 4 p. - Published in : Astron. Soc. Pac. Conf. Proc.: 532 (2022) , pp. 113 Fulltext: PDF; External link: Astronomical Society of the Pacific
In : 30th Astronomical Data Analysis Software and Systems, Granada, Spain, 8 - 12 Nov 2020, pp.113

Registo detalhado - Registos similares

The ESCAPE Dark Matter Test Science Project / Cuoco, Elena (Lund U. (main)) ; Doglioni, Caterina (Pisa, Scuola Normale Superiore ; EGO, Pisa) ; Graf, Kay (Annecy, LAPP ; Savoie U. (main)) ; Lamanna, Giovanni (CERN) ; Meehan, Samuel Ross
A Dark Matter Science Project is being developed in the context of the ESCAPE project (https://projectescape.eu). The goal of this ESCAPE Test Science Project is to highlight the synergies between different communities and experiments searching for dark matter by producing new results and making the necessary data and software tools fully available, in particular focusing on data management, data analysis and computing. [...]
SISSA, 2021 - 4 p. - Published in : PoS TOOLS2020 (2021) 029 Fulltext: PDF;
In : Tools for High Energy Physics and Cosmology, Lyon, France, 2 - 6 Nov 2020, pp.029

Registo detalhado - Registos similares

Machine learning applications in Gravitational Wave research to classify transient signals / Cuoco, Elena (speaker) (EGO-European Gravitational Observatory)
Most of the data collected by Gravitational Wave (GW) interferometers are essentially background noise containing many noise transient signals, which has to be analyzed in a fast and efficient way to increase the detection confidence and to obtain information about likely noise sources. Characterizing the noise transient signals (glitches) is an important task to reduce the impact of transient noise on the detectors. Inspecting glitches manually is a time-consuming and error-prone task and the increase of sensitivity in advanced detectors will lead to more classes of glitches. [...]
2019 - 2997. EP-IT Data science seminars External link: Event details In : Machine learning applications in Gravitational Wave research to classify transient signals

Registo detalhado - Registos similares

Veja também: nomes de autores similares
78	Cuoco, E
15	Cuoco, E.

Interested in being notified about new results for this query?
Set up a personal email alert or subscribe to the RSS feed.

Haven't found what you were looking for? Try your search on other servers:
Cuoco, Elena em Amazon Cuoco, Elena em CERN EDMS Cuoco, Elena em CERN Intranet Cuoco, Elena em CiteSeer Cuoco, Elena em Google Books Cuoco, Elena em Google Scholar Cuoco, Elena em Google Web Cuoco, Elena em IEC	Cuoco, Elena em IHS Cuoco, Elena em INSPIRE Cuoco, Elena em ISO Cuoco, Elena em KISS Books/Journals Cuoco, Elena em KISS Preprints Cuoco, Elena em NEBIS Cuoco, Elena em SLAC Library Catalog Cuoco, Elena em Scirus

CERN Document Server

Access articles, reports and multimedia content in HEP

Main menu

CERN Accelerating science