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 1161–1170 of 1192 papers

TitleStatusHype
GraphPB: Graphical Representations of Prosody Boundary in Speech Synthesis—0
Graph Relation Aware Continual Learning—0
SpaceE: Knowledge Graph Embedding by Relational Linear Transformation in the Entity Space—0
Spaceland Embedding of Sparse Stochastic Graphs—0
What the Vec? Towards Probabilistically Grounded Embeddings—0
Graph Representation Learning on Tissue-Specific Multi-Omics—0
SparGE: Sparse Coding-based Patient Similarity Learning via Low-rank Constraints and Graph Embedding—0
Detection of Correlated Alarms Using Graph Embedding—0
Graph Similarities and Dual Approach for Sequential Text-to-Image Retrieval—0
GraphTTS: graph-to-sequence modelling in neural text-to-speech—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified