Dependency visualising [Bayesian Network]

Thank you for your reply! It would be pretty neat if we can integrate daft with Pyro somehow to aid with debugging. Indeed d is dependent on the data I made a mistake in my plot :slight_smile:

Thanks for the code snippet, so should I always assume independence between variables under the same plate?
Like in the code are a and b independent? I might have misunderstood the docs if they are.
But then why did we need a high_level plate to indicate c and x are independent, but we didn’t need it for a and b?

My confusion arises from the following Pyro’s tutorial on shapes: Is it always safe to assume dependence and this thread: Dependency tracking in pyro

In the second thread, even though both a and b were under a plate, it was mentioned that they are dependent

  with pyro.plate("my_plate1", 2):
        a =  sample('a', Bernoulli(0.5))
        b = sample('b',  Bernoulli(0.5))

… rest of the thread:
a[0] and b[0] are in the same slice (0) and by the first rule above b[0] is assumed to depend on a[0].