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Graph Vertex Embeddings: Distance, Regularization and Community Detection
Graph embeddings have emerged as a powerful tool for representing complex network structures in a low-dimensional space, enabling the use of efficient methods that employ the metric structure in the embedding space as a proxy for the topological structure of the data.
ReGAE: Graph autoencoder based on recursive neural networks
In this paper we address the above challenge with recursive neural networks - the encoder and the decoder.
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