Graph entropy guided Node Embedding Dimension Selection for Graph Neural Networks

被引:0
|
作者
Luo, Gongxu [1 ,2 ]
Li, Jianxin [1 ,2 ]
Su, Jianlin [3 ]
Peng, Hao [1 ]
Yang, Carl [4 ]
Sun, Lichao [5 ]
Yu, Philip S. [6 ]
He, Lifang [5 ]
机构
[1] Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, China
[2] School of Computer Science and Engineering, Beihang University, China
[3] Shenzhen Zhuiyi Technology Co., Ltd, China
[4] Department of Computer Science, Emory University, United States
[5] Department of Computer Science and Engineering, Lehigh University, United States
[6] Department of Computer Science, University of Illinois, Chicago, United States
来源
arXiv | 2021年
关键词
641.1 Thermodynamics - 723.3 Database Systems - 723.4 Artificial Intelligence;
D O I
暂无
中图分类号
学科分类号
摘要
Graph neural networks
引用
收藏
相关论文
共 50 条
  • [1] Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks
    Luo, Gongxu
    Li, Jianxin
    Peng, Hao
    Yang, Carl
    Sun, Lichao
    Yu, Philip S.
    He, Lifang
    PROCEEDINGS OF THE THIRTIETH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2021, 2021, : 2767 - 2774
  • [2] Semantic-guided graph neural network for heterogeneous graph embedding
    Han, Mingjing
    Zhang, Han
    Li, Wei
    Yin, Yanbin
    EXPERT SYSTEMS WITH APPLICATIONS, 2023, 232
  • [3] A-GNN: Anchors-Aware Graph Neural Networks for Node Embedding
    Liu, Chao
    Li, Xinchuan
    Zhao, Dongyang
    Guo, Shaolong
    Kang, Xiaojun
    Dong, Lijun
    Yao, Hong
    QUALITY, RELIABILITY, SECURITY AND ROBUSTNESS IN HETEROGENEOUS SYSTEMS, 2020, 300 : 141 - 153
  • [4] NODE-VARIANT GRAPH FILTERS IN GRAPH NEURAL NETWORKS
    Gama, Fernando
    Anderson, Brendon G.
    Sojoudi, Somayeh
    2022 IEEE DATA SCIENCE AND LEARNING WORKSHOP (DSLW), 2022,
  • [5] Feature selection: Key to enhance node classification with graph neural networks
    Maurya, Sunil Kumar
    Liu, Xin
    Murata, Tsuyoshi
    CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY, 2023, 8 (01) : 14 - 28
  • [6] Visualizing Graph Neural Networks With CorGIE: Corresponding a Graph to Its Embedding
    Liu, Zipeng
    Wang, Yang
    Bernard, Juergen
    Munzner, Tamara
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2022, 28 (06) : 2500 - 2516
  • [7] Learning the Geodesic Embedding with Graph Neural Networks
    Pang, Bo
    Zheng, Zhongtian
    Wang, Guoping
    Wang, Peng-Shuai
    ACM TRANSACTIONS ON GRAPHICS, 2023, 42 (06):
  • [8] A Generalization of Recurrent Neural Networks for Graph Embedding
    Han, Xiao
    Zhang, Chunhong
    Guo, Chenchen
    Ji, Yang
    ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PAKDD 2018, PT II, 2018, 10938 : 247 - 259
  • [9] Exploiting node metadata to predict interactions in bipartite networks using graph embedding and neural networks
    Runghen, Rogini
    Stouffer, Daniel B. B.
    Dalla Riva, Giulio V. V.
    ROYAL SOCIETY OPEN SCIENCE, 2022, 9 (08):
  • [10] Optimal Node Embedding Dimension Selection Using Overall Entropy
    Xu, Xinrun
    Ding, Zhiming
    Wu, Yurong
    Yan, Jin
    Jiang, Shan
    Cui, Qinglong
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING, ICANN 2023, PT IX, 2023, 14262 : 114 - 127