def METHOD_NAME(self, measurement):
    """
    Compute and return the likelihood of a potential update, but don't
    actually perform the update. Assumes state and measurement are time-
    aligned. Useful for gating and calculating costs in assignment problems
    for data association.
    :param: measurement.
    :return: Likelihood of hypothetical update.
    """
    dz, S = self.innovation(measurement)
    return dist.MultivariateNormal(
        torch.zeros(S.size(-1), dtype=S.dtype, device=S.device), S
    ).log_prob(dz)