The field of property testing originated in work on program checking, and has evolved into
an established and very active research area. In this work, we survey the developments of …

Given samples from an unknown distribution, p, is it possible to distinguish whether p
belongs to some class of distributions C versus p being far from every distribution in C? This …

We introduce the notion of a Canonical Tester for a class of properties on distributions, that
is, a tester strong and general enough that" a distribution property in the class is testable if …

Given samples from an unknown multivariate distribution p, is it possible to distinguish
whether p is the product of its marginals versus p being far from every product distribution …

We consider testing and learning problems on causal Bayesian networks as defined by
Pearl (Pearl, 2009). Given a causal Bayesian network M on a graph with n discrete variables …

We study a new framework for property testing of probability distributions, by considering
distribution testing algorithms that have access to a conditional sampling oracle. This is an …

This work initiates a systematic investigation of testing\em high-dimensional structured
distributions by focusing on testing\em Bayesian networks–the prototypical family of directed …

We present a new methodology for proving distribution testing lower bounds, establishing a
connection between distribution testing and the simultaneous message passing (SMP) …

We give a nearly-optimal algorithm for testing uniformity of distributions supported on {–1, 1}
n, which makes many queries to a subcube conditional sampling oracle (Bhattacharyya and …

We show that the square Hellinger distance between two Bayesian networks on the same
directed graph, $ G $, is subadditive with respect to the neighborhoods of $ G $. Namely, if …