Results 31 to 40 of about 18,832 (283)
Quadratic GCN for Graph Classification
CoRR, 2021 Graph Convolutional Networks (GCNs) have been extensively used to classify vertices in graphs and have been shown to outperform other vertex classification methods. GCNs have been extended to graph classification tasks (GCT). In GCT, graphs with different numbers of edges and vertices belong to different classes, and one attempts to predict the graph ...
Omer Nagar +3 more
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The impact of GCN layers on the predictive performance of iPiDA-GCN on .
, 2022 The impact of GCN layers on the predictive performance of iPiDA-GCN on .
Bin Liu (5899) +2 more
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Analyzing GCN Aggregation on GPU
IEEE Access, 2022 Graph convolutional neural networks (GCNs) are emerging neural networks for graph structures that include large features associated with each vertex. The operations of GCN can be divided into two phases - aggregation and combination. While the combination just performs matrix multiplications using trained weights and aggregated features, the ...
Inje Kim +4 more
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, 2019 The official implementation of PU-GCN https://sites.google.com/kaust.edu.sa ...
Li, Guohao +4 more
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IEEE Access, 2022 Graph Convolutional Network (GCN) has achieved significant success in many graph representation learning tasks. GCN usually learns graph representations by performing Neighbor Aggregation (NA) and Feature Transformation (FT) operations.
Dezhi Sun, Man Hu, Zhenyu Li
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Frontiers in Sensors, 2022 In this study a nanocomposite of graphitic carbon nitride-silver polyvinylpyrrolidone (gCN-AgPVP) was fabricated for the electrochemical detection of paracetamol (PAR).
N. Mekgoe, N. Mabuba, K. Pillay
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Spammer detection technology of social network based on graph convolution network
网络与信息安全学报, 2018 In social networks,Spammer send advertisements that are useless to recipients without the recipient's permission,seriously threatening the information security of normal users and the credit system of social networking sites.In order to solve problems of
Qiang QU,Hongtao YU,Ruiyang HUANG
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IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023 Graph Convolutional Network (GCN) excels at EEG recognition by capturing brain connections, but previous studies neglect the important EEG feature itself.
Deng Pan +6 more
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Characterizing and Understanding GCNs on GPU
IEEE Computer Architecture Letters, 2020 To Appear in IEEE Computer Architecture ...
Mingyu Yan +6 more
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DataSheet1_PPA-GCN: A Efficient GCN Framework for Prokaryotic Pathways Assignment.docx
, 2022 With the rapid development of sequencing technology, completed genomes of microbes have explosively emerged. For a newly sequenced prokaryotic genome, gene functional annotation and metabolism pathway assignment are important foundations for all ...
Qi Li (67548) +2 more
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