Is there a way to compute likelihood of a new sample using the Empirical distribution?
import torch from pyro.distributions import empirical samples = torch.randn(100, 5) emp_dist = empirical.Empirical(samples, torch.ones(100)) new_observation = torch.randn(5) emp_dist.log_prob(new_observation)
Currently this code outputs
-inf. I assume because the new observation is not in the samples used to create the distribution.
I’m basically looking for a way to score the “in-distribution-ness” of the
Any suggestions are appreciated.