337 citations · 512 across the 8 of their papers we have counts for
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3 papers · 1 filter
cs.LG2023★ 3 cited
TGNN: A Joint Semi-supervised Framework for Graph-level Classification
Wei Ju, Xiao Luo, Meng Qu +5
This paper studies semi-supervised graph classification, a crucial task with a wide range of applications in social network analysis and bioinformatics. Recent works typically adop…
cs.IR2023★ 68 cited
Learning Graph ODE for Continuous-Time Sequential Recommendation
Yifang Qin, Wei Ju, Hongjun Wu +2
Sequential recommendation aims at understanding user preference by capturing successive behavior correlations, which are usually represented as the item purchasing sequences based…
cs.LG2023★ 337 cited
A Comprehensive Survey on Deep Graph Representation Learning
Wei Ju, Zheng Fang, Yiyang Gu +13
Graph representation learning aims to effectively encode high-dimensional sparse graph-structured data into low-dimensional dense vectors, which is a fundamental task that has been…