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Graph Sampling

Training GNNs or generating graph embeddings requires graph samples.

Papers

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Showing 1–25 of 101 papers

TitleStatusHype
Keyed Chaotic Dynamics for Privacy-Preserving Neural Inference—0
Simple yet Effective Graph Distillation via Clustering—0
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs—0
The Limits of Graph Samplers for Training Inductive Recommender Systems: Extended results—0
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNsCode1
Distributed Graph Neural Network Inference With Just-In-Time Compilation For Industry-Scale Graphs—0
Hierarchical graph sampling based minibatch learning with chain preservation and variance reductionCode0
GraphSOS: Graph Sampling and Order Selection to Help LLMs Understand Graphs Better—0
BMG-Q: Localized Bipartite Match Graph Attention Q-Learning for Ride-Pooling Order Dispatch—0
Physics-Guided Fair Graph Sampling for Water Temperature Prediction in River Networks—0
Towards joint graph learning and sampling set selection from data—0
Graph Sampling for Scalable and Expressive Graph Neural Networks on Homophilic Graphs—0
GCM-Net: Graph-enhanced Cross-Modal Infusion with a Metaheuristic-Driven Network for Video Sentiment and Emotion Analysis—0
Federated Graph Learning with Adaptive Importance-based Sampling—0
Retrofitting Temporal Graph Neural Networks with TransformerCode1
Bearing Fault Diagnosis using Graph Sampling and Aggregation Network—0
Unveiling Privacy Vulnerabilities: Investigating the Role of Structure in Graph Data—0
Edge Sampling of Graphs: Graph Signal Processing Approach With Edge Smoothness—0
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
Accelerating Scientific Discovery with Generative Knowledge Extraction, Graph-Based Representation, and Multimodal Intelligent Graph ReasoningCode3
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
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