GANN: Graph Alignment Neural Network for semi-supervised learning-Reference-Cited by-同舟云学术

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GANN: Graph Alignment Neural Network for semi-supervised learning

Published:2024-10 Issue: Volume:154 Page:110484
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Song Linxuan,Tu Wenxuan,Zhou Sihang,Zhu En

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference35 articles.

1. Semi-supervised classification with graph convolutional networks;Kipf,2016

2. When does self-supervision help graph convolutional networks?;You,2020

3. How to construct corresponding anchors for incomplete multiview clustering;Yu;IEEE Trans. Circuits Syst. Video Technol.,2023

4. Sparse low-rank multi-view subspace clustering with consensus anchors and unified bipartite graph;Yu;IEEE Trans. Neural Netw. Learn. Syst.,2023

5. MobileGCN applied to low-dimensional node feature learning;Dong;Pattern Recognit.,2021

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1. A Cybersecurity Threat Recognition Framework Combining GAN Networks and Semi-Supervised Learning;Applied Mathematics and Nonlinear Sciences;2024-01-01

2. The Cascaded Forward Algorithm for Neural Network Training;2024

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