I’m struggling to work effectively with models that are using the
AutoLaplaceApproximation guide. Unlike the (mutlivariate) normal approximations, you cannot just pull quantiles from the estimated posterior directly, and I am unable to find usage examples in the docs.
I did find the following approach for sampling from the posterior here:
guide = autoguides.AutoLaplaceApproximation(my_model) <fit model> laplace_guide = guide.laplace_approximation() pred = pyro.infer.Predictive(laplace_guide, num_samples=1000)
but it does not work directly with
my_model in my case because the model itself takes 4 tensors of data as arguments. However, when I try and pass the data to the
laplace_guide = guide.laplace_approximation(*data)
I get a
RuntimeError: One of the differentiated Tensors does not require grad
Does anyone have a link to a fully worked example? That is, something that shows how to extract inference from a fitted model using the
AutoLaplaceApproximation or similar guides.