Source code of the "Graph-Bert: Only Attention is Needed for Learning Graph Representations" paper

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Text Data & NLP Graph-Bert
Overview

Graph-Bert

Source code of "Graph-Bert: Only Attention is Needed for Learning Graph Representations".

Please check the script.py as the entry point. We suggest to run the code with Pycharm.

Several toolkits may be needed to run the code (1) pytorch (https://anaconda.org/pytorch/pytorch) (2) sklearn (https://anaconda.org/anaconda/scikit-learn) (3) transformers (https://anaconda.org/conda-forge/transformers) (4) networkx (https://anaconda.org/anaconda/networkx)

Learning results of Graph-Bert with graph-raw residual on Cora dataset.

Learning Results of Graph-Bert with Graph Residual on Cora

Learning results of Graph-Bert with raw residual on Cora dataset.

Learning Results of Graph-Bert with Raw Residual on Cora

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Comments
  • Embedding

    Embedding

    Hi,I'm interested in your work of graphbert. And i want to ask that, in the paper,it said that the WL embedding was calculated by sine and cosine style like Transformer, but I can't find it in this code. in this code,it appears that the WL encodding was calculated by torch.nn.embedding? Thank you!

    opened by shibin2018 0
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