Bayesian Neural Network captures the mean response but not the variance in the training data

How do the posterior weights at different layers look like compared to the true weights? Do you see systematic biases? Too flat? Too peaked?

I checked your model more carefully and indeed a fixed noise should be fine (I didn’t realize it was data you generated). Is the posterior for the noise centered around the correct value of 1?

Also, I am not sure I understand your first plots were you demonstrate the noise issues. Could you explain a bit more what you are plotting?