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arXiv Machine Learning By Dai Hai Nguyen, Koji Tsuda

On a linear fused Gromov-Wasserstein distance for graph structured data

Read the original on arXiv Machine Learning →

arXiv:2203. 04711v2 Announce Type: replace Abstract: We present a framework for embedding graph structured data into a vector space, taking into account node features and topology of a graph into the optimal transport (OT) problem.

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