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message: 'To cite package "DPSynth" in publications use:'
type: software
license: MIT
title: 'DPSynth: Differentially Private Synthetic Data with Guaranteed Utility'
version: 0.1.0
abstract: Differentially private (DP) synthetic data generation for tabular data.
  Provides DP Gaussian mixture models, DP Gaussian copulas, DP histogram marginals
  and a Private Aggregation of Teacher Ensembles (PATE) synthesizer for mixed-type
  data, together with a standardized utility evaluation framework (univariate fidelity,
  propensity score MSE, multivariate dependence, downstream task performance), empirical
  disclosure risk auditing (membership inference, attribute disclosure, record linkage)
  and privacy budget accounting (basic, advanced and Renyi DP composition). The implementation
  follows Dwork and Roth (2014) <https://doi.org/10.1561/0400000042> and Dwork et
  al. (2006) <https://doi.org/10.1007/11681878_14> for the DP mechanisms, Papernot
  et al. (2017) <https://doi.org/10.1145/3133956.3133982> for the PATE synthesizer,
  and Woo et al. (2009) <https://doi.org/10.2202/1557-4679.1203> for the disclosure
  risk evaluation framework.
authors:
- family-names: Bijalwan
  given-names: Mukul
  email: mukulbijalwan555@gmail.com
- family-names: Aggarwal
  given-names: Gunjan
- family-names: Jain
  given-names: Mukul
repository: https://mukulbijalwan.r-universe.dev
repository-code: https://github.com/MukulBijalwan/DPSynth
commit: 1c41d3dd7d344fc01e82d423eafacc225a19c0f3
url: https://github.com/MukulBijalwan/DPSynth
date-released: '2026-09-17'
contact:
- family-names: Bijalwan
  given-names: Mukul
  email: mukulbijalwan555@gmail.com