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1 Ergebnisse
1
WinGNN: Dynamic Graph Neural Networks with Random Gradient ..:
, In:
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
,
Zhu, Yifan
;
Cong, Fangpeng
;
Zhang, Dan
... - p. 3650-3662 , 2023
Link:
https://dl.acm.org/doi/10.1145/3580305.3599551
RT T1
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
: T1
WinGNN: Dynamic Graph Neural Networks with Random Gradient Aggregation Window
UL https://suche.suub.uni-bremen.de/peid=acm-3599551&Exemplar=1&LAN=DE A1 Zhu, Yifan A1 Cong, Fangpeng A1 Zhang, Dan A1 Gong, Wenwen A1 Lin, Qika A1 Feng, Wenzheng A1 Dong, Yuxiao A1 Tang, Jie PB ACM YR 2023 K1 dynamic graph neural networks K1 dynamic graph representation learning K1 multi gradient aggregation K1 temporal encoder-free gnn K1 Theory of computation K1 Design and analysis of algorithms K1 Graph algorithms analysis K1 Dynamic graph algorithms K1 Information systems K1 Information systems applications K1 Data mining SP 3650 OP 3662 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3580305.3599551 DO https://dl.acm.org/doi/10.1145/3580305.3599551 SF ELIB - SuUB Bremen
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