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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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4
GPy/models/sparse_GP_regression.py
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@ -90,9 +90,9 @@ class sparse_GP_regression(GP_regression):
# Computes dL_dKmm TODO: nicer precomputations
self.dL_dKmm = -0.5 * self.beta * self.D * mdot(self.Lmi.T, self.A, self.Lmi) # dB
tmp = self.beta*mdot(self.LBL_inv, self.psi2, self.Kmmi)
self.dL_dKmm = -self.beta * self.D * 0.5 * mdot(self.Lmi.T, self.A, self.Lmi) # dB
self.dL_dKmm += -0.5 * self.D * (- self.LBL_inv - tmp - tmp.T + self.Kmmi) # dC
self.dL_dKmm += -0.5 * self.D * (- self.LBL_inv - tmp - tmp.T + self.Kmmi) # dC #TODO: is tmp PD? save some computations here
tmp = (mdot(self.LBL_inv, self.psi1YYpsi1, self.Kmmi)
- self.beta*mdot(self.G, self.psi2, self.Kmmi))
self.dL_dKmm += -0.5*self.beta2*(tmp + tmp.T - self.G) # dE