diff --git a/gtsam/hybrid/tests/testSerializationHybrid.cpp b/gtsam/hybrid/tests/testSerializationHybrid.cpp
index bb1a492feb..5b06312ba4 100644
--- a/gtsam/hybrid/tests/testSerializationHybrid.cpp
+++ b/gtsam/hybrid/tests/testSerializationHybrid.cpp
@@ -39,112 +39,114 @@ using symbol_shorthand::Z;
 
 using namespace serializationTestHelpers;
 
-// BOOST_CLASS_EXPORT_GUID(Factor, "gtsam_Factor");
-// BOOST_CLASS_EXPORT_GUID(HybridFactor, "gtsam_HybridFactor");
-// BOOST_CLASS_EXPORT_GUID(JacobianFactor, "gtsam_JacobianFactor");
-// BOOST_CLASS_EXPORT_GUID(GaussianConditional, "gtsam_GaussianConditional");
-// BOOST_CLASS_EXPORT_GUID(DiscreteConditional, "gtsam_DiscreteConditional");
-
-// BOOST_CLASS_EXPORT_GUID(DecisionTreeFactor, "gtsam_DecisionTreeFactor");
-// using ADT = AlgebraicDecisionTree<Key>;
-// BOOST_CLASS_EXPORT_GUID(ADT, "gtsam_AlgebraicDecisionTree");
-// BOOST_CLASS_EXPORT_GUID(ADT::Leaf, "gtsam_AlgebraicDecisionTree_Leaf");
-// BOOST_CLASS_EXPORT_GUID(ADT::Choice, "gtsam_AlgebraicDecisionTree_Choice")
-
-// BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor, "gtsam_HybridGaussianFactor");
-// BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor::FactorValuePairs,
-//                         "gtsam_HybridGaussianFactor_Factors");
-// BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor::FactorValuePairs::Leaf,
-//                         "gtsam_HybridGaussianFactor_Factors_Leaf");
-// BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor::FactorValuePairs::Choice,
-//                         "gtsam_HybridGaussianFactor_Factors_Choice");
-
-// BOOST_CLASS_EXPORT_GUID(GaussianFactorGraphValuePair,
-//                         "gtsam_GaussianFactorGraphValuePair");
-
-// BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional,
-//                         "gtsam_HybridGaussianConditional");
-// BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional::Conditionals,
-//                         "gtsam_HybridGaussianConditional_Conditionals");
-// BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional::Conditionals::Leaf,
-//                         "gtsam_HybridGaussianConditional_Conditionals_Leaf");
-// BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional::Conditionals::Choice,
-//                         "gtsam_HybridGaussianConditional_Conditionals_Choice");
-// // Needed since GaussianConditional::FromMeanAndStddev uses it
-// BOOST_CLASS_EXPORT_GUID(noiseModel::Isotropic, "gtsam_noiseModel_Isotropic");
-
-// BOOST_CLASS_EXPORT_GUID(HybridBayesNet, "gtsam_HybridBayesNet");
-
-// /* ****************************************************************************/
-// // Test HybridGaussianFactor serialization.
-// TEST(HybridSerialization, HybridGaussianFactor) {
-//   DiscreteKey discreteKey{M(0), 2};
-
-//   auto A = Matrix::Zero(2, 1);
-//   auto b0 = Matrix::Zero(2, 1);
-//   auto b1 = Matrix::Ones(2, 1);
-//   auto f0 = std::make_shared<JacobianFactor>(X(0), A, b0);
-//   auto f1 = std::make_shared<JacobianFactor>(X(0), A, b1);
-//   std::vector<GaussianFactor::shared_ptr> factors{f0, f1};
-
-//   const HybridGaussianFactor factor(discreteKey, factors);
-
-//   EXPECT(equalsObj<HybridGaussianFactor>(factor));
-//   EXPECT(equalsXML<HybridGaussianFactor>(factor));
-//   EXPECT(equalsBinary<HybridGaussianFactor>(factor));
-// }
-
-// /* ****************************************************************************/
-// // Test HybridConditional serialization.
-// TEST(HybridSerialization, HybridConditional) {
-//   const DiscreteKey mode(M(0), 2);
-//   Matrix1 I = Matrix1::Identity();
-//   const auto conditional = std::make_shared<GaussianConditional>(
-//       GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 0.5));
-//   const HybridConditional hc(conditional);
-
-//   EXPECT(equalsObj<HybridConditional>(hc));
-//   EXPECT(equalsXML<HybridConditional>(hc));
-//   EXPECT(equalsBinary<HybridConditional>(hc));
-// }
-
-// /* ****************************************************************************/
-// // Test HybridGaussianConditional serialization.
-// TEST(HybridSerialization, HybridGaussianConditional) {
-//   const DiscreteKey mode(M(0), 2);
-//   Matrix1 I = Matrix1::Identity();
-//   const auto conditional0 = std::make_shared<GaussianConditional>(
-//       GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 0.5));
-//   const auto conditional1 = std::make_shared<GaussianConditional>(
-//       GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 3));
-//   const HybridGaussianConditional gm(mode, {conditional0, conditional1});
-
-//   EXPECT(equalsObj<HybridGaussianConditional>(gm));
-//   EXPECT(equalsXML<HybridGaussianConditional>(gm));
-//   EXPECT(equalsBinary<HybridGaussianConditional>(gm));
-// }
-
-// /* ****************************************************************************/
-// // Test HybridBayesNet serialization.
-// TEST(HybridSerialization, HybridBayesNet) {
-//   Switching s(2);
-//   HybridBayesNet hbn = *(s.linearizedFactorGraph.eliminateSequential());
-
-//   EXPECT(equalsObj<HybridBayesNet>(hbn));
-//   EXPECT(equalsXML<HybridBayesNet>(hbn));
-//   EXPECT(equalsBinary<HybridBayesNet>(hbn));
-// }
-
-// /* ****************************************************************************/
-// // Test HybridBayesTree serialization.
-// TEST(HybridSerialization, HybridBayesTree) {
-//   Switching s(2);
-//   HybridBayesTree hbt = *(s.linearizedFactorGraph.eliminateMultifrontal());
-
-//   EXPECT(equalsObj<HybridBayesTree>(hbt));
-//   EXPECT(equalsXML<HybridBayesTree>(hbt));
-//   EXPECT(equalsBinary<HybridBayesTree>(hbt));
-// }
+BOOST_CLASS_EXPORT_GUID(Factor, "gtsam_Factor");
+BOOST_CLASS_EXPORT_GUID(HybridFactor, "gtsam_HybridFactor");
+BOOST_CLASS_EXPORT_GUID(JacobianFactor, "gtsam_JacobianFactor");
+BOOST_CLASS_EXPORT_GUID(GaussianConditional, "gtsam_GaussianConditional");
+BOOST_CLASS_EXPORT_GUID(DiscreteConditional, "gtsam_DiscreteConditional");
+
+BOOST_CLASS_EXPORT_GUID(DecisionTreeFactor, "gtsam_DecisionTreeFactor");
+using ADT = AlgebraicDecisionTree<Key>;
+BOOST_CLASS_EXPORT_GUID(ADT, "gtsam_AlgebraicDecisionTree");
+BOOST_CLASS_EXPORT_GUID(ADT::Leaf, "gtsam_AlgebraicDecisionTree_Leaf");
+BOOST_CLASS_EXPORT_GUID(ADT::Choice, "gtsam_AlgebraicDecisionTree_Choice")
+
+BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor, "gtsam_HybridGaussianFactor");
+BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor::FactorValuePairs,
+                        "gtsam_HybridGaussianFactor_Factors");
+BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor::FactorValuePairs::Leaf,
+                        "gtsam_HybridGaussianFactor_Factors_Leaf");
+BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor::FactorValuePairs::Choice,
+                        "gtsam_HybridGaussianFactor_Factors_Choice");
+
+BOOST_CLASS_EXPORT_GUID(GaussianFactorGraphValuePair,
+                        "gtsam_GaussianFactorGraphValuePair");
+BOOST_CLASS_EXPORT_GUID(HybridGaussianProductFactor,
+                        "gtsam_HybridGaussianProductFactor");
+
+BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional,
+                        "gtsam_HybridGaussianConditional");
+BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional::Conditionals,
+                        "gtsam_HybridGaussianConditional_Conditionals");
+BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional::Conditionals::Leaf,
+                        "gtsam_HybridGaussianConditional_Conditionals_Leaf");
+BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional::Conditionals::Choice,
+                        "gtsam_HybridGaussianConditional_Conditionals_Choice");
+// Needed since GaussianConditional::FromMeanAndStddev uses it
+BOOST_CLASS_EXPORT_GUID(noiseModel::Isotropic, "gtsam_noiseModel_Isotropic");
+
+BOOST_CLASS_EXPORT_GUID(HybridBayesNet, "gtsam_HybridBayesNet");
+
+/* ****************************************************************************/
+// Test HybridGaussianFactor serialization.
+TEST(HybridSerialization, HybridGaussianFactor) {
+  DiscreteKey discreteKey{M(0), 2};
+
+  auto A = Matrix::Zero(2, 1);
+  auto b0 = Matrix::Zero(2, 1);
+  auto b1 = Matrix::Ones(2, 1);
+  auto f0 = std::make_shared<JacobianFactor>(X(0), A, b0);
+  auto f1 = std::make_shared<JacobianFactor>(X(0), A, b1);
+  std::vector<GaussianFactor::shared_ptr> factors{f0, f1};
+
+  const HybridGaussianFactor factor(discreteKey, factors);
+
+  EXPECT(equalsObj<HybridGaussianFactor>(factor));
+  EXPECT(equalsXML<HybridGaussianFactor>(factor));
+  EXPECT(equalsBinary<HybridGaussianFactor>(factor));
+}
+
+/* ****************************************************************************/
+// Test HybridConditional serialization.
+TEST(HybridSerialization, HybridConditional) {
+  const DiscreteKey mode(M(0), 2);
+  Matrix1 I = Matrix1::Identity();
+  const auto conditional = std::make_shared<GaussianConditional>(
+      GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 0.5));
+  const HybridConditional hc(conditional);
+
+  EXPECT(equalsObj<HybridConditional>(hc));
+  EXPECT(equalsXML<HybridConditional>(hc));
+  EXPECT(equalsBinary<HybridConditional>(hc));
+}
+
+/* ****************************************************************************/
+// Test HybridGaussianConditional serialization.
+TEST(HybridSerialization, HybridGaussianConditional) {
+  const DiscreteKey mode(M(0), 2);
+  Matrix1 I = Matrix1::Identity();
+  const auto conditional0 = std::make_shared<GaussianConditional>(
+      GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 0.5));
+  const auto conditional1 = std::make_shared<GaussianConditional>(
+      GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 3));
+  const HybridGaussianConditional gm(mode, {conditional0, conditional1});
+
+  EXPECT(equalsObj<HybridGaussianConditional>(gm));
+  EXPECT(equalsXML<HybridGaussianConditional>(gm));
+  EXPECT(equalsBinary<HybridGaussianConditional>(gm));
+}
+
+/* ****************************************************************************/
+// Test HybridBayesNet serialization.
+TEST(HybridSerialization, HybridBayesNet) {
+  Switching s(2);
+  HybridBayesNet hbn = *(s.linearizedFactorGraph.eliminateSequential());
+
+  EXPECT(equalsObj<HybridBayesNet>(hbn));
+  EXPECT(equalsXML<HybridBayesNet>(hbn));
+  EXPECT(equalsBinary<HybridBayesNet>(hbn));
+}
+
+/* ****************************************************************************/
+// Test HybridBayesTree serialization.
+TEST(HybridSerialization, HybridBayesTree) {
+  Switching s(2);
+  HybridBayesTree hbt = *(s.linearizedFactorGraph.eliminateMultifrontal());
+
+  EXPECT(equalsObj<HybridBayesTree>(hbt));
+  EXPECT(equalsXML<HybridBayesTree>(hbt));
+  EXPECT(equalsBinary<HybridBayesTree>(hbt));
+}
 
 /* ************************************************************************* */
 int main() {