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Graph Sampling

Training GNNs or generating graph embeddings requires graph samples.

Papers

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Showing 31–40 of 101 papers

Title	Date	Tasks	Status	Hype	Score
Cooperative Minibatching in Graph Neural Networks	Oct 19, 2023	GPUGraph Sampling	CodeCode Available	0	5
Class-level Structural Relation Modelling and Smoothing for Visual Representation Learning	Aug 8, 2023	Graph SamplingRelation	CodeCode Available	0	5
Hierarchical graph sampling based minibatch learning with chain preservation and variance reduction	Mar 2, 2025	Graph SamplingNode Classification	CodeCode Available	0	5
Joint Network Topology Inference via a Shared Graphon Model	Sep 17, 2022	Graphon EstimationGraph Sampling	CodeCode Available	0	5
Are Negative Samples Necessary in Entity Alignment? An Approach with High Performance, Scalability and Robustness	Aug 11, 2021	Entity AlignmentGraph Sampling	CodeCode Available	0	5
Characterizing the Efficiency of Graph Neural Network Frameworks with a Magnifying Glass	Nov 6, 2022	Graph Neural NetworkGraph Sampling	CodeCode Available	0	5
Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data	Jun 27, 2018	Graph SamplingNode Classification	CodeCode Available	0	5
Accurate, Efficient and Scalable Graph Embedding	Oct 28, 2018	ClusteringGraph Embedding	CodeCode Available	0	5
Learning Dynamic Preference Structure Embedding From Temporal Networks	Nov 23, 2021	Graph Sampling	CodeCode Available	0	5
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs	May 23, 2025	Distributed OptimizationGraph Sampling	—Unverified	0	0

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