Search Results for author: Bei Lin

Found 2 papers, 2 papers with code

Multi-View Graph Representation Learning Beyond Homophily

1 code implementation15 Apr 2023 Bei Lin, You Li, Ning Gui, Zhuopeng Xu, Zhiwu Yu

However, partially due to the irregular non-Euclidean data in graphs, the pretext tasks are generally designed under homophily assumptions and cornered in the low-frequency signals, which results in significant loss of other signals, especially high-frequency signals widespread in graphs with heterophily.

Graph Representation Learning Self-Supervised Learning

Graph Representation Learning Beyond Node and Homophily

1 code implementation3 Mar 2022 You Li, Bei Lin, Binli Luo, Ning Gui

Unsupervised graph representation learning aims to distill various graph information into a downstream task-agnostic dense vector embedding.

Edge Classification Graph Embedding +2

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