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
DuoGAT: Dual Time-oriented Graph Attention Networks for Acc..:
, In:
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
,
Lee, Jongsoo
;
Park, Byeongtae
;
Chae, Dong-Kyu
- p. 1188-1197 , 2023
Link:
https://dl.acm.org/doi/10.1145/3583780.3614857
RT T1 <cTitle>Proceedings of the 32nd ACM International Conference on Information and Knowledge Management</cTitle>: T1 <Title>DuoGAT: Dual Time-oriented Graph Attention Networks for Accurate, Efficient and Explainable Anomaly Detection on Time-series</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3614857&Exemplar=1&LAN=DE A1 Lee, Jongsoo A1 Park, Byeongtae A1 Chae, Dong-Kyu PB ACM YR 2023 K1 anomaly detection K1 explainable AI K1 graph neural networks K1 multivariate time-series K1 Computing methodologies K1 Machine learning K1 Learning paradigms K1 Unsupervised learning K1 Anomaly detection K1 Machine learning approaches K1 Neural networks SP 1188 OP 1197 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3583780.3614857 DO https://dl.acm.org/doi/10.1145/3583780.3614857 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
