Data Augmentation: How do GANs synthesize tabular data in recent studies?

"Data is the new oil" by Clive Humby highlights the importance of data in the 21st century. In this context, data augmentation is one of the AI trends which solves the lack of data for machine learning tasks. It is even more critical when collecting large amounts of data is difficult, especially for tabular data. Moreover, synthetic data help to protect private information contained in the original data (e.g., medical records) while sharing it with other parties and the research community. Existing applications of synthetic data include deepfake[1], oversampling for imbalanced data, and public healthcare records.