Deep Bayesian Nonparametric Factor Analysis
arXiv:2011.04770v1
AI Analysis
This work addresses a challenge in machine learning for researchers, but it appears incremental as it builds on existing factor analysis and deep generative models.
The authors tackled the problem of approximating complex non-factorial distributions in latent codes by proposing a deep generative factor analysis model with a beta process prior, and they presented preliminary results from a scalable stochastic EM algorithm.
We propose a deep generative factor analysis model with beta process prior that can approximate complex non-factorial distributions over the latent codes. We outline a stochastic EM algorithm for scalable inference in a specific instantiation of this model and present some preliminary results.