変分オートエンコーダー(Variational Autoencoder: VAE)
Variational Autoencoders (VAEs) have emerged as one of the most popular approaches to unsupervised learning of complicated distributions. VAEs are appealing because they are built on top of standard function approximators (neural networks), and can be trained with stochastic gradient descent. VAEs have already shown promise in generating many kinds of complicated data, including handwritten digits, faces, house numbers, CIFAR images, physical models of scenes, segmentation, and predicting the future from static images.
from Tutorial on Variational Autoencoders
元論文：Auto-Encoding Variational Bayes
パラメータ推定
点推定(Point estimation)
最尤推定(Maximum likelihood estimation)
MAP推定(maximum a posteriori: MAP)
ベイズ推論(Bayesian Inference)
パラメータ推定のアルゴリズム
点推定(Point estimation)
EMアルゴリズム(Expectation-Maximization Algorithm)
ベイズ推論(Bayesian Inference)
変分べイズ(Variational Bayes; VB)