Download PDFOpen PDF in browserRepresentation Learning on Graphs - A SurveyEasyChair Preprint 45837 pages•Date: November 16, 2020AbstractLearning methods to represent graph nodes as feature vectors is a field that has recently seen a surge in research. Embedding graph nodes as vectors is useful to make graph datasets suitable for use in several downstream machine learning tasks. In this survey, we attempt to present an overview of the various methods found in the literature. Keyphrases: Representation Learning, graphs, node embeddings, survey
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