I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
GNN-Aided Distributed GAN with Partially Observable Social ..:
, In:
2024 IEEE Wireless Communications and Networking Conference (WCNC)
,
Chen, Ming
;
Wang, Shangshang
;
Zhang, Tianyi
.. - p. 1-6 , 2024
Link:
https://doi.org/10.1109/WCNC57260.2024.10570928
RT T1
2024 IEEE Wireless Communications and Networking Conference (WCNC)
: T1
GNN-Aided Distributed GAN with Partially Observable Social Graph
UL https://suche.suub.uni-bremen.de/peid=ieee-10570928&Exemplar=1&LAN=DE A1 Chen, Ming A1 Wang, Shangshang A1 Zhang, Tianyi A1 Shao, Ziyu A1 Yang, Yang YR 2024 SN 1558-2612 K1 Training K1 Energy consumption K1 Uncertainty K1 Image edge detection K1 Distributed databases K1 Generative adversarial networks K1 Prediction algorithms SP 1 OP 6 LK http://dx.doi.org/https://doi.org/10.1109/WCNC57260.2024.10570928 DO https://doi.org/10.1109/WCNC57260.2024.10570928 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)