Causal-Aware Tabular GANs with Reinforcement Learning

Existing tabular data generation methods primarily focus on matching statistical distributions between real and synthetic data, often overlooking the preservation of underlying causal relationships. As a result, generated samples may appear realistic while failing to maintain the causal structure re