Speaker
Mariano Gabitto
(CCB)
Description
In this short tutorial, I will review variational inference (VI), a method to approximate posterior probability distributions through optimization. VI became popular as it provides faster convergence than more traditional sampling methods.
This tutorial aims to provide both an introduction and an overview of recent developments. First, I will provide a review of variational inference. Second, I describe some popular advancements such as stochastic variational inference, and variational autoencoders. During the talk, I will establish some connections with mathematical problems in different centers at Flatiron.
