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Graph Sampling

Training GNNs or generating graph embeddings requires graph samples.

Papers

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Showing 41–50 of 101 papers

TitleStatusHype
Light-weight End-to-End Graph Interest Network for CTR Prediction in E-commerce Search—0
AGS-GNN: Attribute-guided Sampling for Graph Neural NetworksCode0
DiskGNN: Bridging I/O Efficiency and Model Accuracy for Out-of-Core GNN Training—0
A Sampling-based Framework for Hypothesis Testing on Large Attributed GraphsCode0
GLISP: A Scalable GNN Learning System by Exploiting Inherent Structural Properties of Graphs—0
A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs—0
Classification of developmental and brain disorders via graph convolutional aggregation—0
Interpretable A-posteriori Error Indication for Graph Neural Network Surrogate Models—0
Cooperative Minibatching in Graph Neural NetworksCode0
Graph Neural Network for Stress Predictions in Stiffened Panels Under Uniform Loading—0
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