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I gave a tutorial on MCMC methods to some interns last week. And it struck me that although the math is absolutely fascinating, the usefulness of knowing the detailed workings of MCMC was very limited. After all, unless you are part of the PyTorch or TensorFlow dev teams, you really don’t need to know how SGD or ADAM works.
Similarly, you just need to know that your model uses MCMC, but do you really need to know the details of Metropolis-Hastings and or how the cooling schedule works in Simulating Annealing? You would just rely on whatever framework you were using (TFP, PyStan, etc…) to do all that for you, and worry about the high level functional aspects of your model.
Have any of you had to write your own MCMC code in a modeling context, not a software development context?
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