1. (machine learning) a series of invertible variable transformations each with Jacobian that is easy to compute that can be used to relate a complex probability distribution to a simple analytic one (typically a normal distribution)
   "They used normalizing flows to model complex data distributions in their generative model"

Derived forms: normalizing flows

Encyclopedia: Normalizing flow