SGAT: simplicial Graph attention network
Heterogeneous graphs have multiple node and edge types and are semantically richer than homogeneous graphs. To learn such complex semantics, many graph neural network approaches for heterogeneous graphs use metapaths to capture multi-hop interactions between nodes. Typically, features from non-targe...
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Main Authors: | , , |
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Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2022
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/159273 https://www.ijcai.org/proceedings/2022/ |
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Institution: | Nanyang Technological University |
Language: | English |