diff --git a/gtsam/inference/FactorUnordered.h b/gtsam/inference/FactorUnordered.h
index 7a3e36628..8425c81fd 100644
--- a/gtsam/inference/FactorUnordered.h
+++ b/gtsam/inference/FactorUnordered.h
@@ -137,12 +137,13 @@ namespace gtsam {
     /// print only keys
     void printKeys(const std::string& s = "Factor", const KeyFormatter& formatter = DefaultKeyFormatter) const;
 
+  protected:
     /// check equality
     bool equals(const This& other, double tol = 1e-9) const;
 
     /// @}
 
-
+  public:
     /// @name Advanced Interface
     /// @{
 
diff --git a/gtsam/linear/GaussianConditionalUnordered.h b/gtsam/linear/GaussianConditionalUnordered.h
index cebbcd52d..78240594b 100644
--- a/gtsam/linear/GaussianConditionalUnordered.h
+++ b/gtsam/linear/GaussianConditionalUnordered.h
@@ -128,7 +128,7 @@ namespace gtsam {
 
     /** Scale the values in \c gy according to the sigmas for the frontal variables in this
      *  conditional. */
-    void scaleFrontalsBySigma(VectorValuesUnordered& gy) const;
+    __declspec(deprecated) void scaleFrontalsBySigma(VectorValuesUnordered& gy) const;
 
   private:
 
@@ -136,10 +136,8 @@ namespace gtsam {
     friend class boost::serialization::access;
     template<class Archive>
     void serialize(Archive & ar, const unsigned int version) {
-      ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(IndexConditional);
-      ar & BOOST_SERIALIZATION_NVP(matrix_);
-      ar & BOOST_SERIALIZATION_NVP(rsd_);
-      ar & BOOST_SERIALIZATION_NVP(sigmas_);
+      ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(BaseFactor);
+      ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(BaseConditional);
     }
   }; // GaussianConditionalUnordered
 
diff --git a/gtsam/linear/GaussianFactorUnordered.h b/gtsam/linear/GaussianFactorUnordered.h
index 59e3b2e9c..296375088 100644
--- a/gtsam/linear/GaussianFactorUnordered.h
+++ b/gtsam/linear/GaussianFactorUnordered.h
@@ -60,6 +60,24 @@ namespace gtsam {
     /** Return the dimension of the variable pointed to by the given key iterator */
     virtual size_t getDim(const_iterator variable) const = 0;
 
+    /**
+     * Return a dense \f$ [ \;A\;b\; ] \in \mathbb{R}^{m \times n+1} \f$
+     * Jacobian matrix, augmented with b with the noise models baked
+     * into A and b.  The negative log-likelihood is
+     * \f$ \frac{1}{2} \Vert Ax-b \Vert^2 \f$.  See also
+     * GaussianFactorGraph::jacobian and GaussianFactorGraph::sparseJacobian.
+     */
+    virtual Matrix augmentedJacobian() const = 0;
+
+    /**
+     * Return the dense Jacobian \f$ A \f$ and right-hand-side \f$ b \f$,
+     * with the noise models baked into A and b. The negative log-likelihood
+     * is \f$ \frac{1}{2} \Vert Ax-b \Vert^2 \f$.  See also
+     * GaussianFactorGraph::augmentedJacobian and
+     * GaussianFactorGraph::sparseJacobian.
+     */
+    virtual std::pair<Matrix,Vector> jacobian() const = 0;
+
     /** Return the augmented information matrix represented by this GaussianFactorUnordered.
      * The augmented information matrix contains the information matrix with an
      * additional column holding the information vector, and an additional row
diff --git a/gtsam/symbolic/SymbolicFactorUnordered.cpp b/gtsam/symbolic/SymbolicFactorUnordered.cpp
index 6b431438f..02476aed4 100644
--- a/gtsam/symbolic/SymbolicFactorUnordered.cpp
+++ b/gtsam/symbolic/SymbolicFactorUnordered.cpp
@@ -59,4 +59,11 @@ namespace gtsam {
       SymbolicFactorUnordered::FromIterator(orderedKeys.begin() + nFrontals, orderedKeys.end())));
   }
 
+  /* ************************************************************************* */
+  std::pair<boost::shared_ptr<SymbolicConditionalUnordered>, boost::shared_ptr<SymbolicFactorUnordered> >
+    SymbolicFactorUnordered::eliminate(const OrderingUnordered& keys) const
+  {
+
+  }
+
 } // gtsam
diff --git a/gtsam/symbolic/SymbolicFactorUnordered.h b/gtsam/symbolic/SymbolicFactorUnordered.h
index 56775598c..9666e8e3e 100644
--- a/gtsam/symbolic/SymbolicFactorUnordered.h
+++ b/gtsam/symbolic/SymbolicFactorUnordered.h
@@ -29,14 +29,9 @@ namespace gtsam {
   // Forward declarations
   class SymbolicConditionalUnordered;
 
-  /**
-   * SymbolicFactorUnordered serves two purposes.  It is the base class for all linear
-   * factors (GaussianFactor, JacobianFactor, HessianFactor), and also functions
-   * as a symbolic factor, used to do symbolic elimination by JunctionTree.
-   *
-   * It derives from Factor with a key type of Key, an unsigned integer.
-   * \nosubgrouping
-   */
+  /** SymbolicFactorUnordered represents a symbolic factor that specifies graph topology but is not
+   *  associated with any numerical function.
+   *  \nosubgrouping */
   class GTSAM_EXPORT SymbolicFactorUnordered: public FactorUnordered {
 
   public:
@@ -92,7 +87,8 @@ namespace gtsam {
     static SymbolicFactorUnordered FromIterator(KEYITERATOR beginKey, KEYITERATOR endKey) {
       return SymbolicFactorUnordered(Base::FromIterators(beginKey, endKey)); }
 
-    /** Constructor from a collection of keys */
+    /** Constructor from a collection of keys - compatible with boost::assign::list_of and
+     *  boost::assign::cref_list_of */
     template<class CONTAINER>
     static SymbolicFactorUnordered FromKeys(const CONTAINER& keys) {
       return SymbolicFactorUnordered(Base::FromKeys(keys)); }
@@ -105,6 +101,13 @@ namespace gtsam {
     /** Whether the factor is empty (involves zero variables). */
     bool empty() const { return keys_.empty(); }
 
+    /** Eliminate the variables in \c keys, in the order specified in \c keys, returning a
+     *  conditional and marginal. */
+    std::pair<boost::shared_ptr<SymbolicConditionalUnordered>, boost::shared_ptr<SymbolicFactorUnordered> >
+      eliminate(const OrderingUnordered& keys) const;
+
+    /// @}
+
   private:
     /** Serialization function */
     friend class boost::serialization::access;