The way I understand them, in a Deep Gaussian Process, the output of each layer becomes the input to the previous layer. How does one predict on new points using these models? Do I need to call gp.conditional on just the input?

I think you’d have to call gp.conditional for each of the GP layers and feed them into each other. I think it’d be super slow though. You could try using pm.gp.HSGP instead of pm.gp.Latent for this.

`conditional` and Deep Gaussian Processes

Questions v5

bwengals April 17, 2023, 9:44pm 7

thanks @cluhmann. Though I hear that many people are saying that it is the greatest PyMC HSGP notebook made for a PyCon 2022 talk to date.

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`conditional` and Deep Gaussian Processes

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