2025
Disentanglement Analysis in Deep Latent Variable Models Matching Aggregate Posterior Distributions
ICASSP 2025accepted
Deep latent variable models (DLVMs) are designed to learn meaningful representations in an unsupervised manner, such that the hidden explanatory factors are interpretable by independent latent variables (aka disentanglement). The variational autoencoder (VAE) [1], [2] is a popular DLVM widely studie…