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attempted to make sparse models more stable through ordered

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multiplication
This commit is contained in:
James Hensman 2013-03-11 14:47:48 +00:00
parent d512e9a160
commit 4081a1526a
1 changed files with 6 additions and 2 deletions
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8
GPy/models/sparse_GP.py
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@ -103,8 +103,12 @@ class sparse_GP(GP):
self.psi1V = np.dot(self.psi1, self.V)
self.psi1VVpsi1 = np.dot(self.psi1V, self.psi1V.T)
self.C = mdot(self.Lmi.T, self.Bi, self.Lmi)
self.E = mdot(self.C, self.psi1VVpsi1/sf2, self.C.T)
tmp = np.dot(self.Lmi.T, self.LBi.T)
self.C = np.dot(tmp,tmp.T)
#self.C = mdot(self.Lmi.T, self.Bi, self.Lmi)
#self.E = mdot(self.C, self.psi1VVpsi1/sf2, self.C.T)
tmp = np.dot(self.C,self.psi1V/sf)
self.E = np.dot(tmp,tmp.T)
# Compute dL_dpsi # FIXME: this is untested for the heterscedastic + uncertin inputs case
self.dL_dpsi0 = - 0.5 * self.D * (self.likelihood.precision * np.ones([self.N,1])).flatten()