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 451–460 of 1192 papers

TitleStatusHype
Graph-based Multi-view Binary Learning for Image Clustering—0
Graph-based Predictable Feature Analysis—0
Electricity Cost Minimization for Multi-Workflow Allocation in Geo-Distributed Data Centers—0
Histopathology WSI Encoding based on GCNs for Scalable and Efficient Retrieval of Diagnostically Relevant Regions—0
Graph Classification Based on Skeleton and Component Features—0
CTRL: Continuous-Time Representation Learning on Temporal Heterogeneous Information Network—0
Unsupervised Graph Embedding via Adaptive Graph Learning—0
Ego-CNN: An Ego Network-based Representation of Graphs Detecting Critical Structures—0
High Tension Lines: Predicting robustness of high-voltage power-grids to cascading failure using network embedding—0
HKTGNN: Hierarchical Knowledge Transferable Graph Neural Network-based Supply Chain Risk Assessment—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified