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Network Embedding

Network Embedding, also known as "Network Representation Learning", is a collective term for techniques for mapping graph nodes to vectors of real numbers in a multidimensional space. To be useful, a good embedding should preserve the structure of the graph. The vectors can then be used as input to various network and graph analysis tasks, such as link prediction

Source: Tutorial on NLP-Inspired Network Embedding

Papers

Showing 401403 of 403 papers

TitleStatusHype
Unsupervised Attributed Multiplex Network EmbeddingCode0
Collaborative Graph Neural Networks for Attributed Network EmbeddingCode0
CANE: Context-Aware Network Embedding for Relation ModelingCode0
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