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some gradient tidying and a small correction in the natural gradients

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James Hensman 2012-12-16 19:03:08 +00:00
parent 43af1c174d
commit b56de4762e
1 changed files with 4 additions and 6 deletions
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10
GPy/models/uncollapsed_sparse_GP.py
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@ -61,12 +61,10 @@ class uncollapsed_sparse_GP(sparse_GP_regression):
self.dL_dpsi2 = 0.5 * self.beta * self.D * (self.Kmmi - mdot(self.Kmmi,self.q_u_expectation[1],self.Kmmi))
# Compute dL_dKmm
tmp = 0.5*self.beta*mdot(self.psi2,self.Kmmi,self.q_u_expectation[1])
tmp = self.beta*mdot(self.psi2,self.Kmmi,self.q_u_expectation[1]) -np.dot(self.q_u_expectation[0],self.psi1V.T)
tmp += tmp.T
tmp += 0.5*self.D*(-self.beta*self.psi2 - self.Kmm + self.q_u_expectation[1])
tmptmp = - 0.5*np.dot(self.q_u_expectation[0],self.psi1V.T)
tmp += tmptmp + tmptmp.T
self.dL_dKmm = mdot(self.Kmmi,tmp,self.Kmmi)
tmp += self.D*(-self.beta*self.psi2 - self.Kmm + self.q_u_expectation[1])
self.dL_dKmm = 0.5*mdot(self.Kmmi,tmp,self.Kmmi)
def log_likelihood(self):
"""
@ -127,7 +125,7 @@ class uncollapsed_sparse_GP(sparse_GP_regression):
Note that the natural gradient in either is given by the gradient in the other (See Hensman et al 2012 Fast Variational inference in the conjugate exponential Family)
"""
dL_dmmT_S = -0.5*self.Lambda+self.q_u_canonical[1]
dL_dmmT_S = -0.5*self.Lambda-self.q_u_canonical[1]
dL_dm = np.dot(self.Kmmi,self.psi1V) - self.q_u_canonical[0]
#dL_dSim =