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 1041–1050 of 1192 papers

TitleStatusHype
Extrinsic Methods for Coding and Dictionary Learning on Grassmann Manifolds—0
Semantically Smooth Knowledge Graph Embedding—0
FairSR: Fairness-aware Sequential Recommendation through Multi-Task Learning with Preference Graph Embeddings—0
Semantic tradeoff for heterogeneous graph embedding—0
Farspredict: A benchmark dataset for link prediction—0
DyGCN: Dynamic Graph Embedding with Graph Convolutional Network—0
Fast and Scalable Multi-Kernel Encoder Classifier—0
A Novel Regularized Principal Graph Learning Framework on Explicit Graph Representation—0
Fast Computation of Generalized Eigenvectors for Manifold Graph Embedding—0
GLSearch: Maximum Common Subgraph Detection via Learning to Search—0
Show:102550
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified