Variational Inference
[KL Divergence](https://texonom.com/kl-divergence-c7964872f5184a7baaf312605405aef6) [Latent Variable](https://texonom.com/latent-variable-c2bb1127d53444018b2d0eaab231cc6c) 


## Probability version of [Variational Method](https://texonom.com/variational-method-da57d88f392e4a20978a6b7a39fb7350) 
생성 모델은 판별 모델에 비해 intractable 단점을 복잡성을 간단한 함수로 흡수
사전확률과 우도의 파라메터 또한 알고 있지 못하는 경우
> ![](https://www.notion.so/image/https%3A%2F%2Fs3-us-west-2.amazonaws.com%2Fsecure.notion-static.com%2Fb8d97c6b-060c-4435-ae1f-7b78dcbf966b%2FUntitled.png?table=block&id=99cd356d-3f06-4358-a603-d4472b57752f&cache=v2)
> 분포 추정 문제를 [Convex Optimization](https://texonom.com/convex-optimization-d3bdaf9012a34af18743ac995ca00366)  바꾸어준다 

> ![](https://www.notion.so/image/https%3A%2F%2Fs3-us-west-2.amazonaws.com%2Fsecure.notion-static.com%2Fc4169ead-b13a-4dd5-8ca4-4cec1f3c7bdb%2FUntitled.png?table=block&id=6d5dcf78-8bd6-422a-86d9-5f445fcf2e6e&cache=v2)

approximate posterior $p(z|x)$ using $q(z)$ because computing [Posterior](https://texonom.com/posterior-87e0f5df288140c7ba475b0629bdda05) is hard 
### Variational Inference Notion
|Title|
|:-:|
|[Variational parameter](https://texonom.com/variational-parameter-e4eaf4c0bd8046219beb3e8872f459b6)|
|[ELBO](https://texonom.com/elbo-bb7352bbce42480298d501c2ae1076d1)|




> [Variational Inference 알아보기 - MLE, MAP부터 ELBO까지](https://modulabs.co.kr/blog/variational-inference-intro/)

> [변분추론(Variational Inference) · ratsgo's blog](https://ratsgo.github.io/generative%20model/2017/12/19/vi/)





