diff --git a/gtsam/hybrid/HybridGaussianFactorGraph.cpp b/gtsam/hybrid/HybridGaussianFactorGraph.cpp
index 66beb3e4c..a04f5776d 100644
--- a/gtsam/hybrid/HybridGaussianFactorGraph.cpp
+++ b/gtsam/hybrid/HybridGaussianFactorGraph.cpp
@@ -261,6 +261,7 @@ hybridElimination(const HybridGaussianFactorGraph &factors,
       if (!factor) {
         return 0.0;  // If nullptr, return 0.0 probability
       } else {
+        // This is the probability q(μ) at the MLE point.
         double error =
             0.5 * std::abs(factor->augmentedInformation().determinant());
         return std::exp(-error);
diff --git a/gtsam/hybrid/HybridGaussianFactorGraph.h b/gtsam/hybrid/HybridGaussianFactorGraph.h
index 02ebea74a..c448400f0 100644
--- a/gtsam/hybrid/HybridGaussianFactorGraph.h
+++ b/gtsam/hybrid/HybridGaussianFactorGraph.h
@@ -252,8 +252,8 @@ class GTSAM_EXPORT HybridGaussianFactorGraph
   }
 
   /**
-   * @brief Compute the unnormalized probabilities of the continuous variables
-   * for each of the modes.
+   * @brief Compute the unnormalized probabilities P(X | M, Z)
+   * of the continuous variables for each of the mode sequences.
    *
    * @tparam BAYES  Template on the type of Bayes graph, either a bayes net or a
    * bayes tree.
@@ -304,8 +304,6 @@ class GTSAM_EXPORT HybridGaussianFactorGraph
   std::pair<Ordering, Ordering> separateContinuousDiscreteOrdering(
       const Ordering& ordering) const;
 
-  
-
   /**
    * @brief Return a Colamd constrained ordering where the discrete keys are
    * eliminated after the continuous keys.