Tumult Analytics: a robust, easy-to-use, scalable, and expressive framework for differential privacy
Skye Berghel
Philip Bohannon
Damien Desfontaines
Charles Estes
Samuel Haney
Luke Hartman
Michael Hay
Ashwin Machanavajjhala
Tom Magerlein
G. Miklau
Amritha Pai
William Sexton
Ruchit Shrestha

Abstract
In this short paper, we outline the design of Tumult Analytics, a Python framework for differential privacy used at institutions such as the U.S. Census Bureau, the Wikimedia Foundation, or the Internal Revenue Service.
View on arXivComments on this paper