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 471–480 of 1192 papers

TitleStatusHype
AGNN: Alternating Graph-Regularized Neural Networks to Alleviate Over-Smoothing—0
A Comprehensive Survey on Deep Graph Representation Learning—0
Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding—0
Knowledge Graph Embedding with 3D Compound Geometric TransformationsCode0
From axioms over graphs to vectors, and back again: evaluating the properties of graph-based ontology embeddingsCode0
Distributed Graph Embedding with Information-Oriented Random WalksCode0
Joint embedding in Hierarchical distance and semantic representation learning for link prediction—0
Farspredict: A benchmark dataset for link prediction—0
GETT-QA: Graph Embedding based T2T Transformer for Knowledge Graph Question AnsweringCode0
From Wide to Deep: Dimension Lifting Network for Parameter-efficient Knowledge Graph Embedding—0
Show:102550
← PrevPage 48 of 120Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified