Shirin Goshtasbpour

Neural Autoregressive Models and Normalizing Flows

Estimation of probability density of high dimensional complex data distributions is a long-standing challenge in many different fields, including machine learning. Neural Autoregressive Density Estimation (NADE) is a method that estimates data distributions by modeling each term in the probability chain rule with a parameterized function [1]. (1)   The indices in (1) represent an…