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 571–580 of 1192 papers

TitleStatusHype
CompoundE: Knowledge Graph Embedding with Translation, Rotation and Scaling Compound Operations—0
Wasserstein Graph Distance Based on L_1-Approximated Tree Edit Distance between Weisfeiler-Lehman SubtreesCode0
Attributed Abnormality Graph Embedding for Clinically Accurate X-Ray Report Generation—0
Learning to Borrow– Relation Representation for Without-Mention Entity-Pairs for Knowledge Graph CompletionCode0
Time-aware Dynamic Graph Embedding for Asynchronous Structural Evolution—0
Assessing the Effects of Hyperparameters on Knowledge Graph Embedding QualityCode0
Neural Networks in a Product of Hyperbolic Spaces—0
Comprehensive Analysis of Negative Sampling in Knowledge Graph Representation LearningCode0
On the Surprising Behaviour of node2vecCode0
Manifold Graph Signal Restoration using Gradient Graph Laplacian Regularizer—0
Show:102550
← PrevPage 58 of 120Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified