MAP
[Bayes Theorem](https://texonom.com/bayes-theorem-e512b6c0308f4270aaae9ae53060ccab) 


## Maximum A Posteriori
- priori mean ‘**from the earlier**’
- posteriori means ‘**from the later**’
finds the parameters $\tilde{\theta}_{MAP}$ maximizing a posteriori distribution
assume $\theta$ also has some distribution and find optimal $\theta$
We assume a zero-mean Gaussian prior with covariance Σ for parameters $\theta$








