diff --git a/GPy/inference/latent_function_inference/dtc.py b/GPy/inference/latent_function_inference/dtc.py
index 5590a079..a12726e2 100644
--- a/GPy/inference/latent_function_inference/dtc.py
+++ b/GPy/inference/latent_function_inference/dtc.py
@@ -20,7 +20,8 @@ class DTC(LatentFunctionInference):
     def __init__(self):
         self.const_jitter = 1e-6
 
-    def inference(self, kern, X, Z, likelihood, Y, Y_metadata=None):
+    def inference(self, kern, X, Z, likelihood, Y, mean_function=None, Y_metadata=None):
+        assert mean_function is None, "inference with a mean function not implemented"
         assert X_variance is None, "cannot use X_variance with DTC. Try varDTC."
 
         num_inducing, _ = Z.shape
@@ -88,7 +89,8 @@ class vDTC(object):
     def __init__(self):
         self.const_jitter = 1e-6
 
-    def inference(self, kern, X, X_variance, Z, likelihood, Y, Y_metadata):
+    def inference(self, kern, X, Z, likelihood, Y, mean_function=None, Y_metadata=None):
+        assert mean_function is None, "inference with a mean function not implemented"
         assert X_variance is None, "cannot use X_variance with DTC. Try varDTC."
 
         num_inducing, _ = Z.shape
diff --git a/GPy/inference/latent_function_inference/exact_gaussian_inference.py b/GPy/inference/latent_function_inference/exact_gaussian_inference.py
index 1312d36a..312855f7 100644
--- a/GPy/inference/latent_function_inference/exact_gaussian_inference.py
+++ b/GPy/inference/latent_function_inference/exact_gaussian_inference.py
@@ -36,10 +36,12 @@ class ExactGaussianInference(LatentFunctionInference):
             #print "WARNING: N>D of Y, we need caching of L, such that L*L^T = Y, returning Y still!"
             return Y
 
-    def inference(self, kern, X, likelihood, Y, Y_metadata=None):
+    def inference(self, kern, X, likelihood, Y, mean_function=None, Y_metadata=None):
         """
         Returns a Posterior class containing essential quantities of the posterior
         """
+        assert mean_function is None, "inference with a mean function not implemented"
+
         YYT_factor = self.get_YYTfactor(Y)
 
         K = kern.K(X)
diff --git a/GPy/inference/latent_function_inference/expectation_propagation.py b/GPy/inference/latent_function_inference/expectation_propagation.py
index 26144974..ba920569 100644
--- a/GPy/inference/latent_function_inference/expectation_propagation.py
+++ b/GPy/inference/latent_function_inference/expectation_propagation.py
@@ -33,7 +33,8 @@ class EP(LatentFunctionInference):
         # TODO: update approximation in the end as well? Maybe even with a switch?
         pass
 
-    def inference(self, kern, X, likelihood, Y, Y_metadata=None, Z=None):
+    def inference(self, kern, X, likelihood, Y, mean_function=None, Y_metadata=None, Z=None):
+        assert mean_function is None, "inference with a mean function not implemented"
         num_data, output_dim = Y.shape
         assert output_dim ==1, "ep in 1D only (for now!)"
 
diff --git a/GPy/inference/latent_function_inference/expectation_propagation_dtc.py b/GPy/inference/latent_function_inference/expectation_propagation_dtc.py
index 35b1b7dc..466cbbb2 100644
--- a/GPy/inference/latent_function_inference/expectation_propagation_dtc.py
+++ b/GPy/inference/latent_function_inference/expectation_propagation_dtc.py
@@ -64,7 +64,8 @@ class EPDTC(LatentFunctionInference):
         self.old_mutilde, self.old_vtilde = None, None
         self._ep_approximation = None
 
-    def inference(self, kern, X, Z, likelihood, Y, Y_metadata=None):
+    def inference(self, kern, X, Z, likelihood, Y, mean_function=None, Y_metadata=None):
+        assert mean_function is None, "inference with a mean function not implemented"
         num_data, output_dim = Y.shape
         assert output_dim ==1, "ep in 1D only (for now!)"
 
diff --git a/GPy/inference/latent_function_inference/fitc.py b/GPy/inference/latent_function_inference/fitc.py
index a184c6c4..f99b35ff 100644
--- a/GPy/inference/latent_function_inference/fitc.py
+++ b/GPy/inference/latent_function_inference/fitc.py
@@ -18,7 +18,8 @@ class FITC(LatentFunctionInference):
     """
     const_jitter = 1e-6
 
-    def inference(self, kern, X, Z, likelihood, Y, Y_metadata=None):
+    def inference(self, kern, X, Z, likelihood, Y, mean_function=None, Y_metadata=None):
+        assert mean_function is None, "inference with a mean function not implemented"
 
         num_inducing, _ = Z.shape
         num_data, output_dim = Y.shape
diff --git a/GPy/inference/latent_function_inference/laplace.py b/GPy/inference/latent_function_inference/laplace.py
index 05711b0b..4e6ece11 100644
--- a/GPy/inference/latent_function_inference/laplace.py
+++ b/GPy/inference/latent_function_inference/laplace.py
@@ -39,10 +39,11 @@ class Laplace(LatentFunctionInference):
         self.first_run = True
         self._previous_Ki_fhat = None
 
-    def inference(self, kern, X, likelihood, Y, Y_metadata=None):
+    def inference(self, kern, X, likelihood, Y, mean_function=None, Y_metadata=None):
         """
         Returns a Posterior class containing essential quantities of the posterior
         """
+        assert mean_function is None, "inference with a mean function not implemented"
 
         # Compute K
         K = kern.K(X)
diff --git a/GPy/inference/latent_function_inference/svgp.py b/GPy/inference/latent_function_inference/svgp.py
index 1974991b..23d36a14 100644
--- a/GPy/inference/latent_function_inference/svgp.py
+++ b/GPy/inference/latent_function_inference/svgp.py
@@ -6,7 +6,8 @@ from posterior import Posterior
 
 class SVGP(LatentFunctionInference):
 
-    def inference(self, q_u_mean, q_u_chol, kern, X, Z, likelihood, Y, Y_metadata=None, KL_scale=1.0, batch_scale=1.0):
+    def inference(self, q_u_mean, q_u_chol, kern, X, Z, likelihood, Y, mean_function=None, Y_metadata=None, KL_scale=1.0, batch_scale=1.0):
+        assert mean_function is None, "inference with a mean function not implemented"
         num_inducing = Z.shape[0]
         num_data, num_outputs = Y.shape
 
diff --git a/GPy/mappings/linear.py b/GPy/mappings/linear.py
index e172b4e2..6fc91944 100644
--- a/GPy/mappings/linear.py
+++ b/GPy/mappings/linear.py
@@ -33,7 +33,7 @@ class Linear(Mapping):
         return np.dot(X, self.A)
 
     def update_gradients(self, dL_dF, X):
-        self.A.gradient = np.dot( X.T dL_dF)
+        self.A.gradient = np.dot( X.T, dL_dF)
 
     def gradients_X(self, dL_dF, X):
         return np.dot(dL_dF, self.A.T)