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 1101–1110 of 1192 papers

TitleStatusHype
Hierarchical stochastic graphlet embedding for graph-based pattern recognitionCode0
One-Class Kernel Spectral Regression—0
Knowledge Graph Embedding with Numeric Attributes of Entities—0
Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis—0
Exploring the Semantic Content of Unsupervised Graph Embeddings: An Empirical StudyCode0
On representation power of neural network-based graph embedding and beyond—0
What the Vec? Towards Probabilistically Grounded Embeddings—0
GESF: A Universal Discriminative Mapping Mechanism for Graph Representation Learning—0
From Knowledge Graph Embedding to Ontology Embedding? An Analysis of the Compatibility between Vector Space Representations and Rules—0
Knowledge-enriched Two-layered Attention Network for Sentiment Analysis—0
Show:102550
← PrevPage 111 of 120Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified