Correntropy-Induced Wasserstein GCN: Learning Graph Embedding via Domain Adaptation Introduction Graph embedding aims at learning vertex representations in a low-dimensional space by distilling information from a complex structured graph. Recent efforts in graph embedding have been devoted to generalizing the...
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为有效评测该模型对藏文文本的分类性能,自建了较大规模和较高质量的藏文新闻文本公开数据集TNEWS(https://github.com/LG2016/CINO-TextGCN),通过实验发现,CINO-TextGCN在公开数据集TNCC上的准确率为74.20%,在TNEWS上为83.96%。因此,该...
ST-GCN论文简读以及复现,code:https://github.com/yysijie/st-gcn文章目录普通卷积与图卷积普通卷积图卷积数据输入数据结构数据
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Real-time SLAM system with deep features. Contribute to DioVei/GCNv2_SLAM development by creating an account on GitHub.