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首页> 外文期刊>Robotics & Machine Learning Daily News >Reports on Neural Computation Findings from National University of Defense Technology Provide New Insights (On the Explainability of Graph Convolutional Network With Gcn Tangent Kernel)
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Reports on Neural Computation Findings from National University of Defense Technology Provide New Insights (On the Explainability of Graph Convolutional Network With Gcn Tangent Kernel)

机译:国防科技大学神经计算成果报告提供新见解(Gcn Tangent Kernel for Graph Convolutional Network of Plainability of Graph, Convolutional Network)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Computation - Neural Computation. According tonews reporting originating in Changsha, People’s Republic of China, by NewsRx journalists, research stated,“Graph convolutional network (GCN) is a powerful deep model in dealing with graph data. However, theexplainability of GCN remains a difficult problem since the training behaviors for graph neural networks arehard to describe.”
机译:机器人技术与新闻记者新闻编辑机器学习日常调查人员公布新报告计算神经计算。来自长沙,人民共和国NewsRx记者,中国研究说,强大的深度模型在处理图形数据。然而,困难的问题,因为培训行为对神经网络图

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