Towards data augmentation in graph neural network: An overview and evaluation

This publication has 8 references indexed in Scilit:

• Pre-Train and Learn: Preserving Global Information for Graph Neural Networks
  Journal of Computer Science and Technology, 2021
• Graph neural networks in node classification: survey and evaluation
  Machine Vision and Applications, 2021
• Pseudotext Injection and Advance Filtering of Low‐Resource Corpus for Neural Machine Translation
  Computational Intelligence and Neuroscience, 2021
• Benign overfitting in linear regression
  Proceedings of the National Academy of Sciences, 2020
• Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure
  IEEE Transactions on Knowledge and Data Engineering, 2019
• A survey on Image Data Augmentation for Deep Learning
  Journal of Big Data, 2019
• Triangle Lasso for Simultaneous Clustering and Optimization in Graph Datasets
  IEEE Transactions on Knowledge and Data Engineering, 2018
• Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
  IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018