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1graph-adversarial-learning-literature
https://github.com/safe-graph/graph-adversarial-learning-literature
3 years ago by @mengcao
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1Adversarial Attack and Defense on Graph Data: A Survey.
L. Sun, J. Wang, P. Yu, and B. Li. CoRR, (2018)
3 years ago by @mengcao
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2HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification.
R. Ragesh, S. Sellamanickam, A. Iyer, R. Bairi, and V. Lingam. WSDM, (2021)
4 years ago by @mengcao
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2Document and Word Representations Generated by Graph Convolutional Network and BERT for Short Text Classification.
Z. Ye, G. Jiang, Y. Liu, Z. Li, and J. Yuan. ECAI, volume 325 of Frontiers in Artificial Intelligence and Applications, page 2275-2281. IOS Press, (2020)
4 years ago by @mengcao
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2Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification.
L. Hu, T. Yang, C. Shi, H. Ji, and X. Li. EMNLP/IJCNLP (1), page 4820-4829. Association for Computational Linguistics, (2019)
4 years ago by @mengcao
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2Graph Convolutional Networks for Text Classification.
L. Yao, C. Mao, and Y. Luo. AAAI, page 7370-7377. AAAI Press, (2019)
4 years ago by @mengcao
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6Heterogeneous Graph Transformer
Z. Hu, Y. Dong, K. Wang, and Y. Sun. arXiv:2003.01332 cs, stat, (March 2020)arXiv: 2003.01332.
4 years ago by @mengcao
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2Heterogeneous Graph Neural Network
C. Zhang, D. Song, C. Huang, A. Swami, and N. Chawla. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, page 793--803. Anchorage AK USA, ACM, (July 2019)
4 years ago by @mengcao
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3MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding
X. Fu, J. Zhang, Z. Meng, and I. King. Proceedings of The Web Conference 2020, page 2331--2341. (April 2020)arXiv: 2002.01680.
4 years ago by @mengcao
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1Combining Label Propagation and Simple Models Out-performs Graph Neural Networks
Q. Huang, H. He, A. Singh, S. Lim, and A. Benson. arXiv:2010.13993 cs, (November 2020)arXiv: 2010.13993.
4 years ago by @mengcao
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2Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes
K. Sun, Z. Lin, and Z. Zhu. Proceedings of the AAAI Conference on Artificial Intelligence, 34, page 5892--5899. (April 2020)
4 years ago by @mengcao
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2Strategies for Pre-training Graph Neural Networks
W. Hu, B. Liu, J. Gomes, M. Zitnik, P. Liang, V. Pande, and J. Leskovec. arXiv:1905.12265 cs, stat, (February 2020)arXiv: 1905.12265.
4 years ago by @mengcao
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2GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training
J. Qiu, Q. Chen, Y. Dong, J. Zhang, H. Yang, M. Ding, K. Wang, and J. Tang. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, page 1150--1160. (August 2020)arXiv: 2006.09963.
4 years ago by @mengcao
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2GPT-GNN: Generative Pre-Training of Graph Neural Networks
Z. Hu, Y. Dong, K. Wang, K. Chang, and Y. Sun. arXiv:2006.15437 cs, stat, (June 2020)arXiv: 2006.15437.
4 years ago by @mengcao
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1Self-supervised Training of Graph Convolutional Networks
Q. Zhu, B. Du, and P. Yan. arXiv:2006.02380 cs, (June 2020)arXiv: 2006.02380.
4 years ago by @mengcao
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2Self-Supervised Graph Representation Learning via Global Context Prediction
Z. Peng, Y. Dong, M. Luo, X. Wu, and Q. Zheng. arXiv:2003.01604 cs, stat, (March 2020)arXiv: 2003.01604.
4 years ago by @mengcao
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2Contrastive Multi-View Representation Learning on Graphs
K. Hassani, and A. Khasahmadi. arXiv:2006.05582 cs, stat, (June 2020)arXiv: 2006.05582.
4 years ago by @mengcao
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2When Does Self-Supervision Help Graph Convolutional Networks?
Y. You, T. Chen, Z. Wang, and Y. Shen. arXiv:2006.09136 cs, stat, (July 2020)arXiv: 2006.09136.
4 years ago by @mengcao
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1Deep Graph Contrastive Representation Learning
Y. Zhu, Y. Xu, F. Yu, Q. Liu, S. Wu, and L. Wang. arXiv:2006.04131 cs, stat, (July 2020)arXiv: 2006.04131.
4 years ago by @mengcao
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3Graph Contrastive Learning with Augmentations
Y. You, T. Chen, Y. Sui, T. Chen, Z. Wang, and Y. Shen. arXiv:2010.13902 cs, (November 2020)arXiv: 2010.13902.
4 years ago by @mengcao
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2HOW TO FIND YOUR FRIENDLY NEIGHBORHOOD: GRAPH ATTENTION DESIGN WITH SELF-SUPERVISION
D. Kim, and A. Oh. page 25. (2021)
4 years ago by @mengcao
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BibSonomy

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1graph-adversarial-learning-literature

publications (hide)24
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1Adversarial Attack and Defense on Graph Data: A Survey.

2HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification.

2Document and Word Representations Generated by Graph Convolutional Network and BERT for Short Text Classification.

2Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification.

2Graph Convolutional Networks for Text Classification.

6Heterogeneous Graph Transformer

2Heterogeneous Graph Neural Network

3MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding

1Combining Label Propagation and Simple Models Out-performs Graph Neural Networks

2Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes

2Strategies for Pre-training Graph Neural Networks

2GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

2GPT-GNN: Generative Pre-Training of Graph Neural Networks

1Self-supervised Training of Graph Convolutional Networks

2Self-Supervised Graph Representation Learning via Global Context Prediction

2Contrastive Multi-View Representation Learning on Graphs

2When Does Self-Supervision Help Graph Convolutional Networks?

1Deep Graph Contrastive Representation Learning

3Graph Contrastive Learning with Augmentations

2HOW TO FIND YOUR FRIENDLY NEIGHBORHOOD: GRAPH ATTENTION DESIGN WITH SELF-SUPERVISION

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