dpart: Differentially Private Autoregressive Tabular, a General Framework for Synthetic Data Generation. (arXiv:2207.05810v1 [cs.LG])

We propose a general, flexible, and scalable framework dpart, an open source
Python library for differentially private synthetic data generation. Central to
the approach is autoregressive modelling -- breaking the joint data
distribution to a sequence of lower-dimensional conditional distributions,
captured by various methods such as machine learning models (logistic/linear
regression, decision trees, etc.), simple histogram counts, or custom
techniques. The library has been created with a view to serve as a quick and
accessible baseline as well as to …

data framework general lg synthetic data