Add missing minus sign in log score docstring

Author: han-ol

bayesflow/scores/multivariate_normal_score.py

@@ -11,7 +11,7 @@
 
 @serializable(package="bayesflow.scores")
 class MultivariateNormalScore(ParametricDistributionScore):
-    r""":math:`S(\hat p_{\mu, \Sigma}, \theta; k) = \log( \mathcal N (\theta; \mu, \Sigma))`
+    r""":math:`S(\hat p_{\mu, \Sigma}, \theta; k) = -\log( \mathcal N (\theta; \mu, \Sigma))`
 
     Scores a predicted mean and covariance matrix with the log-score of the probability of the materialized value.
     """

bayesflow/scores/parametric_distribution_score.py

@@ -7,7 +7,7 @@
 
 @serializable(package="bayesflow.scores")
 class ParametricDistributionScore(ScoringRule):
-    r""":math:`S(\hat p_\phi, \theta; k) = \log(\hat p_\phi(\theta))`
+    r""":math:`S(\hat p_\phi, \theta; k) = -\log(\hat p_\phi(\theta))`
 
     Base class for scoring a predicted parametric probability distribution with the log-score
     of the probability of the realized value.
@@ -26,7 +26,7 @@ def score(self, estimates: dict[str, Tensor], targets: Tensor, weights: Tensor =
         r"""
         Computes the log-score for a predicted parametric probability distribution given realized **targets**.
 
-        :math:`S(\hat p_\phi, \theta; k) = \log(\hat p_\phi(\theta))`
+        :math:`S(\hat p_\phi, \theta; k) = -\log(\hat p_\phi(\theta))`
         """
         scores = -self.log_prob(x=targets, **estimates)
         score = self.aggregate(scores, weights)