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 751–760 of 1192 papers

TitleStatusHype
Question-Aware Memory Network for Multi-hop Question Answering in Human-Robot Interaction—0
Membership Inference Attacks on Knowledge Graphs—0
Histopathology WSI Encoding based on GCNs for Scalable and Efficient Retrieval of Diagnostically Relevant Regions—0
Modelling Brain Connectivity Networks by Graph Embedding for Dyslexia Diagnosis—0
Combining exogenous and endogenous signals with a semi-supervised co-attention network for early detection of COVID-19 fake tweetsCode0
Multiple Run Ensemble Learning with Low-Dimensional Knowledge Graph EmbeddingsCode0
KI-BERT: Infusing Knowledge Context for Better Language and Domain Understanding—0
Query Driven-Graph Neural Networks for Community Search: From Non-Attributed, Attributed, to Interactive Attributed—0
DyGCN: Dynamic Graph Embedding with Graph Convolutional Network—0
RelWalk - A Latent Variable Model Approach to Knowledge Graph Embedding—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified