SOTAVerified

Graph Embedding

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

( Image credit: GAT )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 701–710 of 1192 papers

TitleStatusHype
A Survey on Embedding Dynamic Graphs—0
Wasserstein Coupled Graph Learning for Cross-Modal Retrieval—0
Dynamic Graph Representation Learning with Fourier Temporal State EmbeddingCode0
Graph Embedding via Topology and Functional Analysis—0
Graph Convolutional Networks for traffic anomalyCode1
On Using Classification Datasets to Evaluate Graph-Level Outlier Detection: Peculiar Observations and New InsightsCode1
Hop-Hop Relation-aware Graph Neural Networks—0
Understanding graph embedding methods and their applications—0
Bipartite Graph Embedding via Mutual Information MaximizationCode1
Unify Local and Global Information for Top-N RecommendationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified