a. bocci
CERN, European Organization for Nuclear Research
Switzerland
- Frontiers in Big Data
- Big Data and AI in High Energy Physics
- Research Topics
- Heterogeneous Computing for AI and Big Data in High Energy Physics
Heterogeneous Computing for AI and Big Data in High Energy Physics
6,271
Total downloads
33k
Total views and downloads
Submit your idea
Select the journal/section where you want your idea to be submitted:
46 Authors
benjamin hawks
Fermi National Accelerator Laboratory
United States
burt holzman
Fermi National Accelerator Laboratory
United States
charles leggett
Lawrence Berkeley National Laboratory
United States
daniele cesini
CNAF-Italian Institute for Nuclear Physics
Italy
daniele d’agostino
IEIIT-National Research Council of Italy
Italy
felice pantaleo
European Organization for Nuclear Research (CERN)
Switzerland
jan kieseler
Experimental Physics Department, European Organization for Nuclear Research (CERN)
Switzerland
javier duarte
Department of Physics, University of California, San Diego
United States
kevin pedro
Department of Physics and Astronomy, Purdue university, West Lafayette
United States
m. kortelainen
Fermi National Accelerator Laboratory
United States
marco rovere
European Organization for Nuclear Research (CERN)
Switzerland
Published in
Frontiers in Big Data
- Big Data and AI in High Energy Physics
Participating Journals
Frontiers in Artificial Intelligence
- 3.0 impact factor
- 6.1 citescore
Impact
- 33kTopic views
- 25kArticle views
- 6,271Article downloads