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Graph Decoupling Attention Markov Networks for Semisupervised Graph Node Classification

  • Published:2022 Issue: Volume: Page:1-15
  • ISSN:2162-237X
  • Container-title:IEEE Transactions on Neural Networks and Learning Systems
  • language:
  • Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Chen JieORCID,Chen ShouzhenORCID,Bai MingyuanORCID,Pu JianORCID,Zhang JunpingORCID,Gao JunbinORCID

Funder

National Natural Science Foundation of China

Shanghai Municipal Science and Technology Major Project

Zhangjiang Laboratory ZJLab

Shanghai Center for Brain Science and Brain-Inspired Technology

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Graph Aggregating-Repelling Network: Do Not Trust All Neighbors in Heterophilic Graphs;Neural Networks;2024-10

2. Cognitive State Detection in Task Context Based on Graph Attention Network During Flight;IEEE Transactions on Systems, Man, and Cybernetics: Systems;2024-09

3. Automatic Design of Deep Graph Neural Networks With Decoupled Mode;IEEE Transactions on Neural Networks and Learning Systems;2024

4. From Node Interaction to Hop Interaction: New Effective and Scalable Graph Learning Paradigm;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06

5. Location-Guided LiDAR-Based Panoptic Segmentation for Autonomous Driving;IEEE Transactions on Intelligent Vehicles;2023-02
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