Hi , I am a beginning learner of the tensorflow probability. After reading the section about
Epistemic Uncertainty on probabilistic regression, I have a query on the posterior sampling. In a variety of articles,
Bayesian inference requires to approximate the posterior distribution. Therefore, I expect the model will include the codes of sampling
algorithm. However, the posterior mean field function only defined a Sequential model and two layers.
Am I mis-understanding or missing something?
Any guidance or advice is much appreciated.
Best regards,
Andy