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linear without caching, derivatives done

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Max Zwiessele 2014-02-21 09:14:31 +00:00
parent 1d722c4f28
commit 0c92fca31a
7 changed files with 71 additions and 54 deletions
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2
GPy/inference/latent_function_inference/var_dtc.py
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@ -70,10 +70,8 @@ class VarDTC(object):
if uncertain_inputs:
grad_dict = {'dL_dKmm': dL_dKmm, 'dL_dpsi0':dL_dpsi0, 'dL_dpsi1':dL_dpsi1, 'dL_dpsi2':dL_dpsi2}
kern.update_gradients_variational(mu=X, S=X_variance, Z=Z, **grad_dict)
else:
grad_dict = {'dL_dKmm': dL_dKmm, 'dL_dKdiag':dL_dpsi0, 'dL_dKnm':dL_dpsi1}
kern.update_gradients_sparse(X=X, Z=Z, **grad_dict)
#get sufficient things for posterior prediction
#TODO: do we really want to do this in the loop?