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
Expressive and Efficient Representation Learning for Rankin..:
, In:
Proceedings of the ACM Web Conference 2023
,
Suresh, Susheel
;
Shrivastava, Mayank
;
Mukherjee, Arko
.. - p. 567-577 , 2023
Link:
https://dl.acm.org/doi/10.1145/3543507.3583476
RT T1
Proceedings of the ACM Web Conference 2023
: T1
Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs
UL https://suche.suub.uni-bremen.de/peid=acm-3583476&Exemplar=1&LAN=DE A1 Suresh, Susheel A1 Shrivastava, Mayank A1 Mukherjee, Arko A1 Neville, Jennifer A1 Li, Pan PB ACM YR 2023 K1 link ranking and representation learning K1 temporal graph neural networks K1 Mathematics of computing K1 Information systems K1 Computing methodologies K1 Information systems applications K1 Theory of computation K1 Theory and algorithms for application domains K1 Artificial intelligence K1 Machine learning K1 Machine learning theory K1 Machine learning approaches K1 Neural networks SP 567 OP 577 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3543507.3583476 DO https://dl.acm.org/doi/10.1145/3543507.3583476 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)