Adversarial random forests generate synthetic epidemiological data that aligns with original findings across six replication studies from German and Canadian cohorts.
Why do tree-based models still outperform deep learning on typical tabular data? Adv Neural Inf Process Syst, 35:507–520
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Can synthetic data reproduce real-world findings in epidemiology? A replication study using adversarial random forests
Adversarial random forests generate synthetic epidemiological data that aligns with original findings across six replication studies from German and Canadian cohorts.