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Author

Ishanu Chattopadhyay

2 papers indexed here

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Review Sep 2026

A Conditional-Distribution Framework for Validating Synthetic Multivariate Data

Statistical validation of synthetic multivariate data requires assessing whether a generator preserves the joint dependence structure of the target population without merely reproducing observed records. We develop a model-agnostic framework based on full conditional distributions. For each coordinate, we normalize the...

H. Dahal, Ishanu Chattopadhyay · 0 citations
Open access Aug 2026

Synthetic Longitudinal Tabular Data Generation via Copula

Synthetic data generation is increasingly used to enable data sharing and secondary analysis while protecting participant privacy, particularly for longitudinal tabular health data, where repeated measures per subject create within-subject dependence that most synthetic data methods are not designed to preserve. Existi...

Hanchang Cai, Wen-Shan Yu, Ruijin Lu et al. · 0 citations

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