22456f4b545572855c766df5eefc9832-Supplemental.pdf

We use t-SNE [37] to project each real/fake record onto a 2-dim space. We summarize the statistics of our datasets as follows: 1. Adult has 22K training, 10K testing records with 6 continuous numerical, 8 categorical, and 1 discrete numerical columns. News has 32K training records, 8K testing records with 45 continuous numerical, 14 categorical, and 0 discrete numerical columns. We introduce one more visualization with Creditin Figure 4. IT-GAN(Q)shows the best similarity between the real and fake points. We compare our method with the following baseline methods, including state-of-the-art VAEs and GANs for tabular data synthesis and our IT-GAN's three variations: 1. Indis a heuristic method that we independently sample a value from each column's groundtruth distribution. We use these baselines' hyperparameters recommended in their original paper and/or GitHub repositories.