郑睿刚
  • 教育程度:博士

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  • 地址:汇星楼406

教程程度 博士 职称
电话 邮箱
地址 汇星楼406 教育经历
工作经历 研究领域
获得荣誉 教学课程
科研成果 期刊
J1. Zheng, R. & Zhuang, X. On the probability estimates of quadrature rules from uniformly
sampled points on spheres. Analysis and Applications, 1–26 (2025).
J2. Li, Jianfei*, Zheng, Ruigang*, Feng, H., Li, M. & Zhuang, X. Permutation equivariant graph framelets for heterophilous graph learning. IEEE Transactions on Neural Networks and Learning Systems (2024).  (*: Equal contribution)
J3. Zheng, R. & Zhuang, X. On the existence and estimates of nested spherical designs. Applied and Computational Harmonic Analysis, 101672 (2024).
J4. Zheng, R., Chen, W. & Feng, G. Semi-supervised node classification via adaptive graph
smoothing networks. Pattern Recognition 124, 108492 (2022).


科研项目

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教育经历

工作经历

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获得荣誉

教学课程

科研成果

  • 期刊 J1. Zheng, R. & Zhuang, X. On the probability estimates of quadrature rules from uniformly sampled points on spheres. Analysis and Applications, 1–26 (2025). J2. Li, Jianfei*, Zheng, Ruigang*, Feng, H., Li, M. & Zhuang, X. Permutation equivariant graph framelets for heterophilous graph learning. IEEE Transactions on Neural Networks and Learning Systems (2024). (*: Equal contribution) J3. Zheng, R. & Zhuang, X. On the existence and estimates of nested spherical designs. Applied and Computational Harmonic Analysis, 101672 (2024). J4. Zheng, R., Chen, W. & Feng, G. Semi-supervised node classification via adaptive graph smoothing networks. Pattern Recognition 124, 108492 (2022).

科研项目