Hey! I’m trying to implement a multidimensional sparse GP but I’m unsure about the syntax for passing arguments to the marginal likelihood function. I’ve managed the following: ` with pm.Model() as model: ℓ = pm.HalfNormal('ℓ', sigma=5) lenght_scale_x = pm.HalfNormal('lenght_scale…

Not sure if this is the underlying problem, but I tried adding the concatenate to KOH_example.py input_1 = [X_1.reshape(-1, 1), c.reshape(-1, 1)] input_1 = np.concatenate(input_1, axis=1) and the model sampled after that without errors (not sure if the traces are OK). Does this help?

Multidimensional Sparse GP

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ckrapu April 4, 2021, 5:18pm 5

I’ve never seen a model with latent inducing points before. Is that something that can be handled in PyMC3? @bwengals

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Multidimensional Sparse GP

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