diff --git a/gtsam/base/Matrix.cpp b/gtsam/base/Matrix.cpp
index 3b21030e7..adf98cf9a 100644
--- a/gtsam/base/Matrix.cpp
+++ b/gtsam/base/Matrix.cpp
@@ -760,7 +760,7 @@ Matrix expm(const Matrix& A, size_t K) {
 
 /* ************************************************************************* */
 Matrix Cayley(const Matrix& A) {
-  size_t n = A.cols();
+  int n = A.cols();
   assert(A.rows() == n);
 
   // original
diff --git a/gtsam/base/treeTraversal-inst.h b/gtsam/base/treeTraversal-inst.h
index e1db89e1b..3edd7d076 100644
--- a/gtsam/base/treeTraversal-inst.h
+++ b/gtsam/base/treeTraversal-inst.h
@@ -216,7 +216,6 @@ namespace gtsam {
      *  To print each node, this function calls the \c print function of the tree nodes. */
     template<class FOREST>
     void PrintForest(const FOREST& forest, std::string str, const KeyFormatter& keyFormatter) {
-      typedef typename FOREST::Node Node;
       PrintForestVisitorPre visitor(keyFormatter);
       DepthFirstForest(forest, str, visitor);
     }
diff --git a/gtsam/inference/inference-inst.h b/gtsam/inference/inference-inst.h
index d21098844..434b705f2 100644
--- a/gtsam/inference/inference-inst.h
+++ b/gtsam/inference/inference-inst.h
@@ -75,10 +75,6 @@ namespace gtsam {
     FastVector<typename TREE::sharedFactor>
     EliminateTree(RESULT& result, const TREE& tree, const typename TREE::Eliminate& function)
     {
-      // Typedefs
-      typedef typename TREE::sharedNode sharedNode;
-      typedef typename TREE::sharedFactor sharedFactor;
-
       // Do elimination using a depth-first traversal.  During the pre-order visit (see
       // eliminationPreOrderVisitor), we store a pointer to the parent data (where we'll put the
       // remaining factor) and reserve a vector of factors to store the children elimination
diff --git a/gtsam/linear/JacobianFactor.cpp b/gtsam/linear/JacobianFactor.cpp
index 139f726bd..e18055edc 100644
--- a/gtsam/linear/JacobianFactor.cpp
+++ b/gtsam/linear/JacobianFactor.cpp
@@ -620,7 +620,7 @@ namespace gtsam {
         model_ = noiseModel::Constrained::MixedSigmas(model_->sigmas().tail(remainingRows));
       else
         model_ = noiseModel::Diagonal::Sigmas(model_->sigmas().tail(remainingRows));
-      assert(model_->dim() == Ab_.rows());
+      assert(model_->dim() == (size_t)Ab_.rows());
     }
     gttoc(remaining_factor);