Graph Neural Networks for Node Classification (English)
- New search for: Tang, Jian
- New search for: Liao, Renjie
- New search for: Wu, Lingfei
- New search for: Cui, Peng
- New search for: Pei, Jian
- New search for: Zhao, Liang
- New search for: Tang, Jian
- New search for: Liao, Renjie
In:
Graph Neural Networks: Foundations, Frontiers, and Applications
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Chapter: 4
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41-61
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2022
- Article/Chapter (Book) / Electronic Resource
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Title:Graph Neural Networks for Node Classification
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Contributors:Wu, Lingfei ( editor ) / Cui, Peng ( editor ) / Pei, Jian ( editor ) / Zhao, Liang ( editor ) / Tang, Jian ( author ) / Liao, Renjie ( author )
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Published in:Graph Neural Networks: Foundations, Frontiers, and Applications ; Chapter: 4 ; 41-61
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Publisher:
- New search for: Springer Nature Singapore
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Place of publication:Singapore
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Publication date:2022-01-03
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Size:21 pages
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ISBN:
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DOI:
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Type of media:Article/Chapter (Book)
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Type of material:Electronic Resource
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Language:English
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Keywords:
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Source:
Table of contents eBook
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 1
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Representation LearningZhao, Liang / Wu, Lingfei / Cui, Peng / Pei, Jian et al. | 2022
- 2
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Graph Representation LearningCui, Peng / Wu, Lingfei / Pei, Jian / Zhao, Liang / Wang, Xiao et al. | 2022
- 3
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Graph Neural NetworksWu, Lingfei / Cui, Peng / Pei, Jian / Zhao, Liang / Song, Le et al. | 2022
- 4
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Graph Neural Networks for Node ClassificationTang, Jian / Liao, Renjie et al. | 2022
- 5
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The Expressive Power of Graph Neural NetworksLi, Pan / Leskovec, Jure et al. | 2022
- 6
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Graph Neural Networks: ScalabilityMa, Hehuan / Rong, Yu / Huang, Junzhou et al. | 2022
- 7
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Interpretability in Graph Neural NetworksLiu, Ninghao / Feng, Qizhang / Hu, Xia et al. | 2022
- 8
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Graph Neural Networks: Adversarial RobustnessGünnemann, Stephan et al. | 2022
- 9
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Graph Neural Networks: Graph ClassificationMorris, Christopher et al. | 2022
- 10
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Graph Neural Networks: Link PredictionZhang, Muhan et al. | 2022
- 11
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Graph Neural Networks: Graph GenerationLiao, Renjie et al. | 2022
- 12
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Graph Neural Networks: Graph TransformationGuo, Xiaojie / Wang, Shiyu / Zhao, Liang et al. | 2022
- 13
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Graph Neural Networks: Graph MatchingLing, Xiang / Wu, Lingfei / Wu, Chunming / Ji, Shouling et al. | 2022
- 14
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Graph Neural Networks: Graph Structure LearningChen, Yu / Wu, Lingfei et al. | 2022
- 15
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Dynamic Graph Neural NetworksKazemi, Seyed Mehran et al. | 2022
- 16
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Heterogeneous Graph Neural NetworksShi, Chuan et al. | 2022
- 17
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Graph Neural Networks: AutoMLZhou, Kaixiong / Liu, Zirui / Duan, Keyu / Hu, Xia et al. | 2022
- 18
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Graph Neural Networks: Self-supervised LearningWang, Yu / Jin, Wei / Derr, Tyler et al. | 2022
- 19
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Graph Neural Networks in Modern Recommender SystemsChu, Yunfei / Yao, Jiangchao / Zhou, Chang / Yang, Hongxia et al. | 2022
- 20
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Graph Neural Networks in Computer VisionTang, Siliang / Zhang, Wenqiao / Mu, Zongshen / Shen, Kai / Li, Juncheng / Li, Jiacheng / Wu, Lingfei et al. | 2022
- 21
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Graph Neural Networks in Natural Language ProcessingLiu, Bang / Wu, Lingfei et al. | 2022
- 22
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Graph Neural Networks in Program AnalysisAllamanis, Miltiadis et al. | 2022
- 23
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Graph Neural Networks in Software MiningMcMillan, Collin et al. | 2022
- 24
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GNN-based Biomedical Knowledge Graph Mining in Drug DevelopmentSu, Chang / Hou, Yu / Wang, Fei et al. | 2022
- 25
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Graph Neural Networks in Predicting Protein Function and InteractionsKabir, Anowarul / Shehu, Amarda et al. | 2022
- 26
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Graph Neural Networks in Anomaly DetectionWang, Shen / Yu, Philip S. et al. | 2022
- 27
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Graph Neural Networks in Urban IntelligenceLi, Yanhua / Zhou, Xun / Pan, Menghai et al. | 2022