SOTAVerified

Graph Embedding

Graph embeddings learn a mapping from a network to a vector space, while preserving relevant network properties.

( Image credit: GAT )

Papers

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Showing 1141–1150 of 1192 papers

TitleStatusHype
graph2vec: Learning Distributed Representations of GraphsCode1
Discriminative Covariance Oriented Representation Learning for Face Recognition With Image Sets—0
Using Locally Corresponding CAD Models for Dense 3D Reconstructions From a Single Image—0
An experimental study of graph-based semi-supervised classification with additional node information—0
Poincaré Embeddings for Learning Hierarchical RepresentationsCode1
Active Learning for Graph EmbeddingCode0
Graph Embedding Techniques, Applications, and Performance: A SurveyCode0
Learning Spatiotemporal-Aware Representation for POI Recommendation—0
struc2vec: Learning Node Representations from Structural IdentityCode0
Learning Combinatorial Optimization Algorithms over GraphsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified