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Ruize Shi

2 accepted papers

2024

An Efficient Subgraph-Inferring Framework for Large-Scale Heterogeneous Graphs

AAAI 2024technical

Heterogeneous Graph Neural Networks (HGNNs) play a vital role in advancing the field of graph representation learning by addressing the complexities arising from diverse data types and interconnected relationships in real-world scenarios. However, traditional HGNNs face challenges when applied to la…

2021

Temporal Heterogeneous Information Network Embedding

IJCAI 2021poster

Heterogeneous information network (HIN) embedding, learning the low-dimensional representation of multi-type nodes, has been applied widely and achieved excellent performance. However, most of the previous works focus more on static heterogeneous networks or learning node embedding within specific s…

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