SOTAVerified

Graph Embedding

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

( Image credit: GAT )

Papers

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Showing 1001–1010 of 1192 papers

TitleStatusHype
Learning Cross-Domain Representation with Multi-Graph Neural Network—0
GLEE: Geometric Laplacian Eigenmap EmbeddingCode0
Knowledge Graph Embedding Bi-Vector Models for Symmetric Relation—0
Toward Understanding The Effect of Loss Function on The Performance of Knowledge Graph Embedding—0
LogicENN: A Neural Based Knowledge Graphs Embedding Model with Logical Rules—0
Scalable Graph Embeddings via Sparse Transpose Proximities—0
TraceWalk: Semantic-based Process Graph Embedding for Consistency Checking—0
Graph U-NetsCode0
Language in Our Time: An Empirical Analysis of Hashtags—0
Vertex Nomination, Consistent Estimation, and Adversarial Modification—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified