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1 Ergebnisse
1
Breaking the Limit of Graph Neural Networks by Improving th..:
, In:
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining
,
Suresh, Susheel
;
Budde, Vinith
;
Neville, Jennifer
.. - p. 1541-1551 , 2021
Link:
https://dl.acm.org/doi/10.1145/3447548.3467373
RT T1 <cTitle>Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining</cTitle>: T1 <Title>Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3467373&Exemplar=1&LAN=DE A1 Suresh, Susheel A1 Budde, Vinith A1 Neville, Jennifer A1 Li, Pan A1 Ma, Jianzhu PB ACM YR 2021 K1 graph neural networks K1 mixing patterns K1 representation learning K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Logical and relational learning K1 Statistical relational learning K1 Modeling and simulation K1 Simulation theory K1 Network science K1 Artificial intelligence K1 Knowledge representation and reasoning SP 1541 OP 1551 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3447548.3467373 DO https://dl.acm.org/doi/10.1145/3447548.3467373 SF ELIB - SuUB Bremen
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