GraphANGEL: Adaptive aNd Structure-Aware Sampling on Graph NEuraL Networks

Author:

Peng Jingshu1,Shen Yanyan2,Chen Lei1

Affiliation:

1. The Hong Kong University of Science and Technology,Dept. of Computer Science and Engineering

2. Shanghai Jiao Tong University,Dept. of Computer Science and Engineering

Funder

National Key Research and Development Program of China

Publisher

IEEE

Reference42 articles.

1. Centrality in social networks conceptual clarification

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3. Policy-GNN: Aggregation Optimization for Graph Neural Networks

4. Distance encoding: Design provably more powerful neural networks for graph representation learning;l;NeurlPS,2020

5. Scaling graph neural networks with approximate pagerank;b;KDD ’20,0

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Survey on Graph Representation Learning Methods;ACM Transactions on Intelligent Systems and Technology;2024-01-16

2. ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware Sampling;Proceedings of the ACM on Management of Data;2023-12-08

3. NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams;Proceedings of the VLDB Endowment;2023-11

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