diff --git a/oodeel/methods/mahalanobis.py b/oodeel/methods/mahalanobis.py
index e32d215..3b29ca7 100644
--- a/oodeel/methods/mahalanobis.py
+++ b/oodeel/methods/mahalanobis.py
@@ -74,9 +74,9 @@ def _fit_to_dataset(self, fit_dataset: DatasetType) -> None:
                 / _zero_f_cls.shape[0]
             )
             if mean_cov is None:
-                mean_cov = (len(_features_cls) / len(features)) * cov_cls
+                mean_cov = (len(_features_cls) / len(features[0])) * cov_cls
             else:
-                mean_cov += (len(_features_cls) / len(features)) * cov_cls
+                mean_cov += (len(_features_cls) / len(features[0])) * cov_cls
 
         # pseudo-inverse of the mean covariance matrix
         self._pinv_cov = self.op.pinv(mean_cov)
diff --git a/oodeel/methods/rmds.py b/oodeel/methods/rmds.py
index c0f5b2f..b08ecf8 100644
--- a/oodeel/methods/rmds.py
+++ b/oodeel/methods/rmds.py
@@ -96,7 +96,7 @@ def _score_tensor(self, inputs: TensorType) -> Tuple[np.ndarray]:
 
         # take the highest score for each sample
         gaussian_score_corrected = self.op.max(
-            gaussian_score_bg - gaussian_score_p, dim=1
+            gaussian_score_p - gaussian_score_bg, dim=1
         )
         return -self.op.convert_to_numpy(gaussian_score_corrected)