SOTAVerified

Entity Embeddings

Entity Embeddings is a technique for applying deep learning to tabular data. It involves representing the categorical data of an information systems entity with multiple dimensions.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–110 of 151 papers

TitleStatusHype
Relation Extraction with Contextualized Relation Embedding (CRE)Code0
DisenE: Disentangling Knowledge Graph Embeddings—0
Content-Based Personalized Recommender System Using Entity Embeddings—0
Entity Embedding as Game Representation—0
DensE: An Enhanced Non-commutative Representation for Knowledge Graph Embedding with Adaptive Semantic HierarchyCode0
Dual Graph Embedding for Object-Tag LinkPrediction on the Knowledge Graph—0
Neural Entity Linking: A Survey of Models Based on Deep Learning—0
Interpretable Entity Representations through Large-Scale Typing—0
Leveraging Prior Knowledge for Protein-Protein Interaction Extraction with Memory Network—0
Improving Entity Linking by Modeling Latent Entity Type Information—0
Show:102550
← PrevPage 11 of 16Next →

No leaderboard results yet.