Sampling data or approximating probabilistic densities is one of the core problems in modern statistics, especially in Bayesian statistic. Beside of MCMC, Variational Inference is one of the two typical Bayesian approaches solving this problem. It leverages the Variational Inference algorithm to develop many recent powerful methods and models: Stochastic Variational Inference, Variational Autoencoder... This… Continue reading Variational Inference algorithm
Tag: bayesian
Getting started with Bayesian Inference
Bayesian inference is an important technique in statistics, particularly in the analysis of a sequence of data. It has a wide range of contributions, including science, engineering, medicine, finance, etc. It can be used to explained mechanisms inside modern techniques, such as regularization in Deep Learning, building structure of Probabilistic Graphical Models, and also a… Continue reading Getting started with Bayesian Inference
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