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GNN-PIM: A Processing-in-Memory Architecture for Graph Neural Networks
2020Graph neural networks (GNNs) have attracted increasing interests in recent years. Due to the poor data locality and huge data movement during GNN inference, it is challenging to employ GNN to process large-scale graphs. Fortunately, processing-in-memory (PIM) architecture has been widely investigated as a promising approach to address the “Memory Wall”.
Zhao Wang +6 more
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GNN-EA: Graph Neural Network with Evolutionary Algorithm
2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2022Yun Huang, Chaobo Zhang, Junli Wang 0001
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Fp-Gnn: Adaptive Fpga Accelerator for Graph Neural Networks
SSRN Electronic Journal, 2022Teng Tian +5 more
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CC-GNN: A Community and Contraction-based Graph Neural Network
2022 IEEE International Conference on Data Mining (ICDM), 2022Zhiyuan Li +3 more
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AIC-GNN: Adversarial information completion for graph neural networks
Information Sciences, 2023Quanmin Wei +4 more
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Genetic-GNN: Evolutionary architecture search for Graph Neural Networks
Knowledge-Based Systems, 2022Min Shi 0001 +6 more
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Multiphysical graph neural network (MP-GNN) for COVID-19 drug design
Briefings in Bioinformatics, 2022Xiang Liu, Kelin Xia
exaly
LR-GNN: a graph neural network based on link representation for predicting molecular associations
Briefings in Bioinformatics, 2022Han Zhang, Shenwei Huang, Yanbin Yin
exaly
HITS-GNN: A Simplified Propagation Scheme for Graph Neural Networks
2022 IEEE International Conference on Big Data (Big Data), 2022Mehak Khan +4 more
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