Data as of Jul 25, 2026 · Based on 2,718,867 AI responses across 9,511 prompts · See how Parse measures this
ctdGAN is a Conditional Generative Adversarial Network designed to synthesize artificial tabular data and alleviate class imbalance in tabular datasets. It uses an initial space partitioning step to assign cluster labels, then generates samples via probabilistic sampling while optimizing a loss function sensitive to both cluster and class mispredictions.
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