How to Set Parameters Distribution For Bayesian Neural Network With PyMC3

Questions
4

Thank simon_o :grinning: .

  1. Would you provide me more information about the prior distribution setting (e.g. some literatures, weblink, etc.)?

  2. “pm.HalfNormal” seems to have no the "mean " parameters setting, which is linked to the variable “act_out”. So how could I use HalfNormal?

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  3. I calculate 95% confidence like this:

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  4. Based on the question #3, I have another question about how to judge the rationality of 95% confidence interval? Since the confidence interval is calculated from the posterior predictive samples, the number
    of samples for sample_ppc() may be vital for the correctness of confidence interval . And what is the principle of sample_ppc()? Does it sample from the distribution space formed by the trace (which is generated from pm.sample() )? If it does, what is the sample method used?

Look forward to your kind reply ~