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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
Graph Sampling for Matrix Completion Using Recurrent Gershgorin Disc Shift—0
Graph sampling for node embedding—0
Graph Sampling for Scalable and Expressive Graph Neural Networks on Homophilic Graphs—0
Graph sampling with determinantal processes—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
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