2026
Generating High-Diversity Synthetic Tabular Data via Less-Constrained Prior
IJCAI 2026
Generating high-quality synthetic tabular data, regarding fidelity, diversity, and utility, is crucial for many practical purposes. Recent tabular data synthesis methods, including two-stage generative modeling approaches, have achieved this with nearly perfect fidelity. However, we observe that the