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Social Influence Prediction with Train and Test Time Augmentation for Graph Neural Networks
[article]
2021
arXiv
pre-print
Data augmentation has been widely used in machine learning for natural language processing and computer vision tasks to improve model performance. However, little research has studied data augmentation on graph neural networks, particularly using augmentation at both train- and test-time. Inspired by the success of augmentation in other domains, we have designed a method for social influence prediction using graph neural networks with train- and test-time augmentation, which can effectively
arXiv:2104.11641v1
fatcat:uojnwjdahvcnhakb2widuc27ka