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1 Ergebnisse
1
DyTed: Disentangled Representation Learning for Discrete-ti..:
, In:
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
,
Zhang, Kaike
;
Cao, Qi
;
Fang, Gaolin
... - p. 3309-3320 , 2023
Link:
https://dl.acm.org/doi/10.1145/3580305.3599319
RT T1 <cTitle>Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</cTitle>: T1 <Title>DyTed: Disentangled Representation Learning for Discrete-time Dynamic Graph</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3599319&Exemplar=1&LAN=DE A1 Zhang, Kaike A1 Cao, Qi A1 Fang, Gaolin A1 Xu, Bingbing A1 Zou, Hongjian A1 Shen, Huawei A1 Cheng, Xueqi PB ACM YR 2023 K1 disentangled representation learning K1 dynamic graphs K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Learning latent representations K1 Information systems K1 World Wide Web K1 Web applications K1 Social networks SP 3309 OP 3320 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3580305.3599319 DO https://dl.acm.org/doi/10.1145/3580305.3599319 SF ELIB - SuUB Bremen
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