Is there a way to compute likelihood of a new sample using the Empirical distribution?
Example:
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 new_observation
.
Any suggestions are appreciated.