diff --git a/gtsam/inference/EliminationTree.h b/gtsam/inference/EliminationTree.h
index e2dab8b80..82480f99e 100644
--- a/gtsam/inference/EliminationTree.h
+++ b/gtsam/inference/EliminationTree.h
@@ -110,8 +110,8 @@ public:
   bool equals(const EliminationTree& other, double tol = 1e-9) const;
 
   /** Eliminate the factors to a Bayes Net
-   * @param function The function to use to eliminate, see the static member
-   * functions of GaussianFactorGraph
+   * @param function The function to use to eliminate, see the namespace functions
+   * in GaussianFactorGraph.h
    * @return The BayesNet resulting from elimination
    */
   typename BayesNet::shared_ptr eliminate(Eliminate function) const;
diff --git a/gtsam/inference/JunctionTree.h b/gtsam/inference/JunctionTree.h
index f4e591b70..f1e85db0b 100644
--- a/gtsam/inference/JunctionTree.h
+++ b/gtsam/inference/JunctionTree.h
@@ -30,6 +30,13 @@
 namespace gtsam {
 
 	/**
+	 * In gtsam a junction tree is an intermediate data structure in multifrontal
+	 * variable elimination.  Each node is a cluster of factors, along with a
+	 * clique of variables that are eliminated all at once.  The tree structure and
+	 * elimination method are exactly analagous to the EliminationTree, except that
+	 * in the JunctionTree, at each node multiple variables are eliminated at the same
+	 * time.
+	 *
 	 * A junction tree (or clique-tree) is a cluster-tree where each node k represents a
 	 * clique (maximal fully connected subset) of an associated chordal graph, such as a
 	 * chordal Bayes net resulting from elimination. In GTSAM the BayesTree is used to
@@ -41,15 +48,17 @@ namespace gtsam {
 
 	public:
 
-		// In a junction tree each cluster is associated with a clique
+		/// In a junction tree each cluster is associated with a clique
 		typedef typename ClusterTree<FG>::Cluster Clique;
-		typedef typename Clique::shared_ptr sharedClique;
+		typedef typename Clique::shared_ptr sharedClique; ///< Shared pointer to a clique
 
+		/// The BayesTree type produced by elimination
 		typedef class BayesTree<typename FG::FactorType::ConditionalType> BayesTree;
 
+		/// Shared pointer to this class
 		typedef boost::shared_ptr<JunctionTree<FG> > shared_ptr;
 
-		// And we will frequently refer to a symbolic Bayes tree
+		/// We will frequently refer to a symbolic Bayes tree, used to find the clique structure
 		typedef gtsam::BayesTree<IndexConditional> SymbolicBayesTree;
 
 	private:
@@ -73,13 +82,29 @@ namespace gtsam {
 		/** Default constructor */
 		JunctionTree() {}
 
-		/** Construct from a factor graph.  Computes a variable index. */
-		JunctionTree(const FG& fg);
+		/** Named constructor to build the junction tree of a factor graph.  Note
+	   * that this has to compute the column structure as a VariableIndex, so if you
+	   * already have this precomputed, use the JunctionTree(const FG&, const VariableIndex&)
+	   * constructor instead.
+	   * @param factorGraph The factor graph for which to build the elimination tree
+	   */
+		JunctionTree(const FG& factorGraph);
 
-		/** Construct from a factor graph and a pre-computed variable index. */
+		/** Construct from a factor graph and pre-computed variable index.
+		 * @param factorGraph The factor graph for which to build the junction tree
+		 * @param structure The set of factors involving each variable.  If this is not
+		 * precomputed, you can call the JunctionTree(const FG&)
+		 * constructor instead.
+		 */
 		JunctionTree(const FG& fg, const VariableIndex& variableIndex);
 
-		// eliminate the factors in the subgraphs
+		/** Eliminate the factors in the subgraphs to produce a BayesTree.
+		 * @param function The function used to eliminate, see the namespace functions
+		 * in GaussianFactorGraph.h
+		 * @param cache Whether to cache the intermediate elimination factors for use in ISAM2 - this
+		 * should always be false when called outside of ISAM2 (this will be fixed in the future).
+		 * @return The BayesTree resulting from elimination
+		 */
 		typename BayesTree::sharedClique eliminate(typename FG::Eliminate function,
 				bool cache = false) const;
 
diff --git a/gtsam/linear/GaussianFactor.h b/gtsam/linear/GaussianFactor.h
index 6fb25c106..7f4b90748 100644
--- a/gtsam/linear/GaussianFactor.h
+++ b/gtsam/linear/GaussianFactor.h
@@ -11,8 +11,8 @@
 
 /**
  * @file    GaussianFactor.h
- * @brief   Linear Factor....A Gaussian
- * @brief   linearFactor
+ * @brief   A factor with a quadratic error function - a Gaussian
+ * @brief   GaussianFactor
  * @author  Richard Roberts, Christian Potthast
  */
 
@@ -34,7 +34,8 @@ namespace gtsam {
   template<class C> class BayesNet;
 
   /**
-   * Base Class for a linear factor.
+   * An abstract virtual base class for JacobianFactor and HessianFactor.
+   * A GaussianFactor has a quadratic error function.
    * GaussianFactor is non-mutable (all methods const!).
    * The factor value is exp(-0.5*||Ax-b||^2)
    */
diff --git a/gtsam/linear/GaussianFactorGraph.h b/gtsam/linear/GaussianFactorGraph.h
index a55b679f6..921cb7958 100644
--- a/gtsam/linear/GaussianFactorGraph.h
+++ b/gtsam/linear/GaussianFactorGraph.h
@@ -32,7 +32,8 @@ namespace gtsam {
 
 	struct SharedDiagonal;
 
-  /** unnormalized error */
+  /** unnormalized error
+   * \todo Make this a member function - affects SubgraphPreconditioner */
   template<class FACTOR>
   double gaussianError(const FactorGraph<FACTOR>& fg, const VectorValues& x) {
     double total_error = 0.;
@@ -42,13 +43,15 @@ namespace gtsam {
     return total_error;
   }
 
-  /** return A*x-b */
+  /** return A*x-b
+   * \todo Make this a member function - affects SubgraphPreconditioner */
   template<class FACTOR>
   Errors gaussianErrors(const FactorGraph<FACTOR>& fg, const VectorValues& x) {
     return *gaussianErrors_(fg, x);
   }
 
-  /** shared pointer version */
+  /** shared pointer version
+   * \todo Make this a member function - affects SubgraphPreconditioner */
   template<class FACTOR>
   boost::shared_ptr<Errors> gaussianErrors_(const FactorGraph<FACTOR>& fg, const VectorValues& x) {
     boost::shared_ptr<Errors> e(new Errors);