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I think the gradients bug in the sparse GP model is due to Kmm being unstable to invert. REducing M in some of the examples really helps

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James Hensman 2012-12-02 12:32:20 +00:00
parent d71ad99db9
commit 1c60e50fed
3 changed files with 6 additions and 4 deletions
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3
GPy/examples/sparse_GP_regression_demo.py
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@ -12,6 +12,7 @@ import GPy
np.random.seed(2)
pb.ion()
N = 500
M = 5
######################################
## 1 dimensional example
@ -26,7 +27,7 @@ noise = GPy.kern.white(1)
kernel = rbf + noise
# create simple GP model
m1 = GPy.models.sparse_GP_regression(X,Y,kernel, M = 10)
m1 = GPy.models.sparse_GP_regression(X, Y, kernel, M=M)
# contrain all parameters to be positive
m1.constrain_positive('(variance|lengthscale|precision)')