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🚀 The feature, motivation and pitch
In large graphs with more than ten million edges, the need for edge sampling is inevitable. Hopefully, GLT can support sampling based on edge weights, so as to better utilize edge features.
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- Implement weighted random walks rusty1s/pytorch_cluster#140
DGL:node2vec random walk and top-k sampling - https://docs.dgl.ai/en/0.8.x/api/python/dgl.sampling.html#neighbor-sampling
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