pbdl-book/bayesian-intro.md
2021-04-04 21:48:43 +08:00

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Introduction to Posterior Inference
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more complex models -> fit data better , but overfit & dont generalize
-> posterior (distrib) inference
std NNs do MLE for weights
"theoretically justifiable" ie correct thing to do -> "posterior inference"
extremely difficult
useful for uncertainty! esp interesting in phys setting
first example here with airfoils, extension from {doc}`supervised-airfoils`