diff --git a/GPy/examples/uncollapsed_GP_demo.py b/GPy/examples/uncollapsed_GP_demo.py
new file mode 100644
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--- /dev/null
+++ b/GPy/examples/uncollapsed_GP_demo.py
@@ -0,0 +1,32 @@
+# Copyright (c) 2012, GPy authors (see AUTHORS.txt).
+# Licensed under the BSD 3-clause license (see LICENSE.txt)
+
+
+import numpy as np
+"""
+Sparse Gaussian Processes regression with an RBF kernel, 
+using the uncollapsed sparse GP (where the distribution of the 
+inducing points is explicitley represented)
+"""
+import pylab as pb
+import numpy as np
+import GPy
+np.random.seed(2)
+pb.ion()
+N = 500
+M = 20
+
+# sample inputs and outputs
+X = np.random.uniform(-3.,3.,(N,1))
+Y = np.sin(X)+np.random.randn(N,1)*0.05
+
+kernel = GPy.kern.rbf(1) + GPy.kern.white(1)
+
+# create simple GP model
+m = GPy.models.uncollapsed_sparse_GP(X, Y, kernel=kernel, M=M)#, X_uncertainty=np.zeros_like(X)+0.01)
+
+# contrain all parameters to be positive
+m.ensure_default_constraints()
+m.checkgrad()
+# optimize and plot
+m.plot()