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Graph Sampling

Training GNNs or generating graph embeddings requires graph samples.

Papers

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Showing 76–100 of 101 papers

TitleStatusHype
Fast Graph Sampling for Short Video Summarization using Gershgorin Disc Alignment—0
Federated Graph Learning with Adaptive Importance-based Sampling—0
FedGraph: Federated Graph Learning with Intelligent Sampling—0
Folded Graph Signals: Sensing with Unlimited Dynamic Range—0
GCM-Net: Graph-enhanced Cross-Modal Infusion with a Metaheuristic-Driven Network for Video Sentiment and Emotion Analysis—0
GDM: Dual Mixup for Graph Classification with Limited Supervision—0
GLISP: A Scalable GNN Learning System by Exploiting Inherent Structural Properties of Graphs—0
Gophormer: Ego-Graph Transformer for Node Classification—0
GraphSOS: Graph Sampling and Order Selection to Help LLMs Understand Graphs Better—0
GraphBGS: Background Subtraction via Recovery of Graph Signals—0
Graph Neural Network for Stress Predictions in Stiffened Panels Under Uniform Loading—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
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
MD-GCN: A Multi-Scale Temporal Dual Graph Convolution Network for Traffic Flow Prediction—0
Neighborhood Random Walk Graph Sampling for Regularized Bayesian Graph Convolutional Neural Networks—0
Neuro-Symbolic Procedural Planning with Commonsense Prompting—0
Accelerating Graph Sampling for Graph Machine Learning using GPUs—0
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