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For: Xie Y, Yao C, Gong M, Chen C, Qin A. Graph convolutional networks with multi-level coarsening for graph classification. Knowledge-Based Systems 2020;194:105578. [DOI: 10.1016/j.knosys.2020.105578] [Cited by in Crossref: 17] [Cited by in F6Publishing: 19] [Article Influence: 5.7] [Reference Citation Analysis]
Number Citing Articles
1 Wang T, Yang J, Xiao Y, Wang J, Wang Y, Zeng X, Wang Y, Peng J. DFinder: a novel end-to-end graph embedding-based method to identify drug-food interactions. Bioinformatics 2023;39. [PMID: 36579885 DOI: 10.1093/bioinformatics/btac837] [Reference Citation Analysis]
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6 Wang Y, Yan J, Ye X, Qi Z, Wang J, Geng Y. GIS partial discharge pattern recognition via a novel capsule deep graph convolutional network. IET Generation Trans & Dist 2022;16:2903-12. [DOI: 10.1049/gtd2.12508] [Reference Citation Analysis]
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9 Chen X, Zhou F, Trajcevski G, Bonsangue M. Multi-view learning with distinguishable feature fusion for rumor detection. Knowledge-Based Systems 2022;240:108085. [DOI: 10.1016/j.knosys.2021.108085] [Cited by in Crossref: 2] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
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11 Wan Y, Chen Z, Hu F, Liu Y, Packianather M, Wang R. Exploiting Knowledge Graph for Multi-faceted Conceptual Modelling using GCN. Procedia Computer Science 2022;200:1174-1183. [DOI: 10.1016/j.procs.2022.01.317] [Reference Citation Analysis]
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13 Yang B, Kang Y, Zhang L, Li H. GGAC: Multi-relational image gated GCN with attention convolutional binary neural tree for identifying disease with chest X-rays. Pattern Recognition 2021;120:108113. [DOI: 10.1016/j.patcog.2021.108113] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
14 Zhang X, Yang Y, Zhai D, Li T, Chu J, Wang H. Local2Global: Unsupervised multi-view deep graph representation learning with Nearest Neighbor Constraint. Knowledge-Based Systems 2021;231:107439. [DOI: 10.1016/j.knosys.2021.107439] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
15 Wu L, Wang D, Song K, Feng S, Zhang Y, Yu G. Dual-view hypergraph neural networks for attributed graph learning. Knowledge-Based Systems 2021;227:107185. [DOI: 10.1016/j.knosys.2021.107185] [Cited by in Crossref: 6] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
16 Liu X, Wei W, Feng X, Cao X, Sun D. Graph classification based on skeleton and component features. Knowledge-Based Systems 2021;228:107301. [DOI: 10.1016/j.knosys.2021.107301] [Reference Citation Analysis]
17 Liu W, Gong M, Tang Z. ETINE: Enhanced Textual Information Network Embedding. Knowledge-Based Systems 2021;220:106917. [DOI: 10.1016/j.knosys.2021.106917] [Reference Citation Analysis]
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19 Cheng S, Zhang L, Jin B, Zhang Q, Lu X, You M, Tian X. GraphMS: Drug Target Prediction Using Graph Representation Learning with Substructures. Applied Sciences 2021;11:3239. [DOI: 10.3390/app11073239] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
20 Park C, Han J, Yu H. Deep multiplex graph infomax: Attentive multiplex network embedding using global information. Knowledge-Based Systems 2020;197:105861. [DOI: 10.1016/j.knosys.2020.105861] [Cited by in Crossref: 16] [Cited by in F6Publishing: 17] [Article Influence: 5.3] [Reference Citation Analysis]