ML Paper Challenge Day 38, 39 — Auto-Encoding Variational Bayes
1 min readMay 20, 2020
Day 38–39: 2020.05.19–20
Paper: Auto-Encoding Variational Bayes
Category: Model/Unsupervised Learning
SGVB (Stochastic Gradient Variational Bayes) estimator
- efficient approximate posterior inference in almost any model with continuous latent variables and/or parameters
- straightforward to optimize using standard stochastic gradient ascent techniques.
Auto-Encoding VB (AEVB) algorithm -> variational auto-encoder
- make inference and learning especially efficient by using the SGVB estimator to optimize a recognition model
- -> perform very efficient approximate posterior inference using simple ancestral sampling
- -> efficiently learn the model parameters, without the need of expensive iterative inference…
