WARNING: This article may be obsoleteThis post was published in 2021-12-13. Obviously, expired content is less useful to users if it has already pasted its expiration date.
This article is categorized as "Garbage" . It should NEVER be appeared in your search engine's results.Table of Contents
正定矩阵/ positive-definite matrix
🔗 [正定矩阵 - 维基百科，自由的百科全书] https://zh.wikipedia.org/zh/%E6%AD%A3%E5%AE%9A%E7%9F%A9%E9%98%B5
Multivariate Gaussian写法规范
来自：🔗 [gaussians.pdf] https://cs229.stanford.edu/section/gaussians.pdf，和 🔗 [top.dvi] http://people.eecs.berkeley.edu/~jordan/courses/260-spring10/other-readings/chapter13.pdf
[mathjax-d]p(x ; \mu, \Sigma)=\frac{1}{(2 \pi)^{n / 2}|\Sigma|^{1 / 2}} \exp \left(-\frac{1}{2}(x-\mu)^{T} \Sigma^{-1}(x-\mu)\right)[/mathjax-d]被写为：[mathjax]X \sim \mathcal{N}(\mu, \Sigma)[/mathjax]，同时，这个表达式也会被写为：
[mathjax-d]p(x \mid \mu, \Sigma)=\frac{1}{(2 \pi)^{n / 2}|\Sigma|^{1 / 2}} \exp \left(-\frac{1}{2}(x-\mu)^{T} \Sigma^{-1}(x-\mu)\right)[/mathjax-d]Completing the square
● 用于Multivariate Gaussian
🔗 [top.dvi] http://people.eecs.berkeley.edu/~jordan/courses/260-spring10/other-readings/chapter13.pdf
似乎并没有用到completing the square 🔗 [Deriving the conditional distributions of a multivariate normal distribution - Cross Validated] https://stats.stackexchange.com/questions/30588/deriving-the-conditional-distributions-of-a-multivariate-normal-distribution
🔗 [probability - Conditional expectation of a bivariate normal distribution - Mathematics Stack Exchange] https://math.stackexchange.com/questions/1531865/conditional-expectation-of-a-bivariate-normal-distribution
●（待补充）
贝叶斯定理又忘了
preview1 preview2 🔗 [怎样用非数学语言讲解贝叶斯定理（Bayes's theorem）？ - 知乎] https://www.zhihu.com/question/19725590
推导过程：🔗 [贝叶斯公式的理解及简单推导小白皮皮-CSDN博客贝叶斯公式推导] https://blog.csdn.net/weixin_41938903/article/details/105566524
另附自己更喜欢的推导方式：
GP, GPR, Bayesian Regression
🔗 [高斯过程和高斯过程回归 - 知乎] https://zhuanlan.zhihu.com/p/100443773
Bayesian cheat sheet
🔗 [bayes_manuscripts.pdf] http://www2.stat.duke.edu/~rcs46/books/bayes_manuscripts.pdf
PCA和SVD（鸽了）
（鸽了）
