Where does Deep Learning come in?
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In particular, variational inference is a family of techniques that makes these kinds of problems computationally tractable. It shows up everywhere from variational autoencoders, to time-series state-space modeling, to reinforcement learning.
If you want to learn more, I recommend reading Murphy's textbooks on ML: https://probml.github.io/pml-book/book2.html