Representative & Fair Synthetic Data. - Paul Tiwald; Alexandra Ebert; Dániel T. Soukup (CoRR, 2021)

Strong statistical parity through fair synthetic data. - Ivona Krchova; Michael Platzer; Paul Tiwald (CoRR, 2023)

TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data. - Paul Tiwald; Ivona Krchova; Andrey Sidorenko; Mariana Vargas Vieyra; Mario Scriminaci; Michael Platzer (CoRR, 2025)

Benchmarking Synthetic Tabular Data: A Multi-Dimensional Evaluation Framework. - Andrey Sidorenko; Michael Platzer; Mario Scriminaci; Paul Tiwald (CoRR, 2025)

Improving Predictions on Highly Unbalanced Data Using Open Source Synthetic Data Upsampling. - Ivona Krchova; Michael Platzer; Paul Tiwald (CoRR, 2025)

Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN. - Andrey Sidorenko; Paul Tiwald (CoRR, 2025)