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

Questions

BlueMan66 April 8, 2021, 5:34pm 7

Yes!! This Helps, Thanks!!!

Topic		Replies	Views
Gaussian Process used to model varying intercepts in GLM Questions	13	1512	October 9, 2019
Sparse GP with linear covariate? Questions	2	613	August 3, 2021
Multivariate Gaussian Processes Questions	2	585	July 27, 2020
Multidimensional MarginalSparse throws with a simple example - "Random variables detected in the logp graph" v5 bug , gaussian_process , modeling	5	1048	October 5, 2022
2d classification with GP, problem Questions	2	894	June 21, 2017

Multidimensional Sparse GP

Related topics