opendp 0.14.2-dev.20260401.2

A library of differential privacy algorithms for the statistical analysis of sensitive private data.
@article{awan2023canonical,
  author    = {Jordan Awan and Salil Vadhan},
  title     = {Canonical Noise Distributions and Private Hypothesis Tests},
  volume    = {51},
  journal   = {The Annals of Statistics},
  number    = {2},
  publisher = {Institute of Mathematical Statistics},
  pages     = {547 -- 572},
  year      = {2023}
}

@article{Awan_Slavkovic_2020,
  title   = {Differentially Private Inference for Binomial Data},
  volume  = {10},
  number  = {1},
  journal = {Journal of Privacy and Confidentiality},
  author  = {Awan, Jordan Alexander and Slavkovic, Aleksandra},
  year    = {2020}
}

@article{dong2019gaussian,
  author  = {Dong, Jinshuo and Roth, Aaron and Su, Weijie J.},
  title   = {{Gaussian Differential Privacy}},
  journal = {Journal of the Royal Statistical Society Series B: Statistical Methodology},
  volume  = {84},
  number  = {1},
  pages   = {3-37},
  year    = {2022},
  issn    = {1369-7412}
}