Nonlinear ICA

Identifiable VAE

August 12, 2024
Deep Learning
Nonlinear ICA, VAE

Identifiable VAE (iVAE) [1] is a variant of the Variational Autoencoder (VAE) model with the primary goal of making this model “identifiable.” This means that iVAE ensures that the latent variables \(z\) it learns are unique (up to permutation), unaffected by unwanted transformations such as permutation or nonlinear transformation. Below is a detailed explanation of the structure and functioning of iVAE. 1. Basics of Identifiability in Machine Learning # Identifiability in machine learning refers to the ability to uniquely determine the latent variables \(z\) from the observed data \(x\). ...