diff --git a/gtsam/discrete/DiscreteFactorGraph.cpp b/gtsam/discrete/DiscreteFactorGraph.cpp
index f8e1b4bb8..b4b65f885 100644
--- a/gtsam/discrete/DiscreteFactorGraph.cpp
+++ b/gtsam/discrete/DiscreteFactorGraph.cpp
@@ -144,6 +144,23 @@ namespace gtsam {
         boost::dynamic_pointer_cast<DiscreteConditional>(lookup), max);
   }
 
+  /* ************************************************************************ */
+  // sumProduct is just an alias for regular eliminateSequential.
+  DiscreteBayesNet DiscreteFactorGraph::sumProduct(
+      OptionalOrderingType orderingType) const {
+    gttic(DiscreteFactorGraph_sumProduct);
+    auto bayesNet = BaseEliminateable::eliminateSequential(orderingType);
+    return *bayesNet;
+  }
+
+  DiscreteLookupDAG DiscreteFactorGraph::sumProduct(
+      const Ordering& ordering) const {
+    gttic(DiscreteFactorGraph_sumProduct);
+    auto bayesNet =
+        BaseEliminateable::eliminateSequential(ordering, EliminateForMPE);
+    return DiscreteLookupDAG::FromBayesNet(*bayesNet);
+  }
+
   /* ************************************************************************ */
   // The max-product solution below is a bit clunky: the elimination machinery
   // does not allow for differently *typed* versions of elimination, so we
diff --git a/gtsam/discrete/DiscreteFactorGraph.h b/gtsam/discrete/DiscreteFactorGraph.h
index 1ba39ff9d..2e9b40823 100644
--- a/gtsam/discrete/DiscreteFactorGraph.h
+++ b/gtsam/discrete/DiscreteFactorGraph.h
@@ -132,11 +132,28 @@ class GTSAM_EXPORT DiscreteFactorGraph
       const std::string& s = "DiscreteFactorGraph",
       const KeyFormatter& formatter = DefaultKeyFormatter) const override;
 
+  /**
+   * @brief Implement the sum-product algorithm
+   *
+   * @param orderingType : one of COLAMD, METIS, NATURAL, CUSTOM
+   * @return DiscreteBayesNet encoding posterior P(X|Z)
+   */
+  DiscreteBayesNet sumProduct(
+      OptionalOrderingType orderingType = boost::none) const;
+
+  /**
+   * @brief Implement the sum-product algorithm
+   *
+   * @param ordering
+   * @return DiscreteBayesNet encoding posterior P(X|Z)
+   */
+  DiscreteLookupDAG sumProduct(const Ordering& ordering) const;
+
   /**
    * @brief Implement the max-product algorithm
    *
    * @param orderingType : one of COLAMD, METIS, NATURAL, CUSTOM
-   * @return DiscreteLookupDAG::shared_ptr DAG with lookup tables
+   * @return DiscreteLookupDAG DAG with lookup tables
    */
   DiscreteLookupDAG maxProduct(
       OptionalOrderingType orderingType = boost::none) const;
@@ -145,7 +162,7 @@ class GTSAM_EXPORT DiscreteFactorGraph
    * @brief Implement the max-product algorithm
    *
    * @param ordering
-   * @return DiscreteLookupDAG::shared_ptr `DAG with lookup tables
+   * @return DiscreteLookupDAG `DAG with lookup tables
    */
   DiscreteLookupDAG maxProduct(const Ordering& ordering) const;
 
diff --git a/gtsam/discrete/tests/testDiscreteFactorGraph.cpp b/gtsam/discrete/tests/testDiscreteFactorGraph.cpp
index f4819dab5..63f5b7319 100644
--- a/gtsam/discrete/tests/testDiscreteFactorGraph.cpp
+++ b/gtsam/discrete/tests/testDiscreteFactorGraph.cpp
@@ -154,6 +154,16 @@ TEST(DiscreteFactorGraph, test) {
   auto actualMPE = graph.optimize();
   EXPECT(assert_equal(mpe, actualMPE));
   EXPECT_DOUBLES_EQUAL(9, graph(mpe), 1e-5);  // regression
+
+  // Test sumProduct alias with all orderings:
+  auto mpeProbability = expectedBayesNet(mpe);
+  EXPECT_DOUBLES_EQUAL(0.28125, mpeProbability, 1e-5);  // regression
+  for (Ordering::OrderingType orderingType :
+       {Ordering::COLAMD, Ordering::METIS, Ordering::NATURAL,
+        Ordering::CUSTOM}) {
+    auto bayesNet = graph.sumProduct(orderingType);
+    EXPECT_DOUBLES_EQUAL(mpeProbability, bayesNet(mpe), 1e-5);
+  }
 }
 
 /* ************************************************************************* */