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Graph Sampling

Training GNNs or generating graph embeddings requires graph samples.

Papers

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Showing 71–80 of 101 papers

TitleStatusHype
The Limits of Graph Samplers for Training Inductive Recommender Systems: Extended results—0
Towards joint graph learning and sampling set selection from data—0
Unsupervised Learning of Morphology with Graph Sampling—0
Impression-Informed Multi-Behavior Recommender System: A Hierarchical Graph Attention Approach—0
Interpretable A-posteriori Error Indication for Graph Neural Network Surrogate Models—0
Keyed Chaotic Dynamics for Privacy-Preserving Neural Inference—0
Learning Large-scale Network Embedding from Representative Subgraph—0
Learning Parameters for Balanced Index Influence Maximization—0
Light-weight End-to-End Graph Interest Network for CTR Prediction in E-commerce Search—0
Little Ball of Fur: A Python Library for Graph Sampling—0
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