I have a model involving a multinomial likelihood with multiple GPs as my prior (the GPs should have different covariance hyperparameters). I’ve heard that for loops are usually frowned upon when defining a model. Is there a way to define multiple GPs while avoiding a for loop? How ‘bad’ is it if it…

There’s nothing too bad with that loop, you are just automating the creation of 8 separate variables. Loops are generally discouraged in the case where you can use a single variable tensor instead of 100s individual variables, but your case might fall more in the “premature optimization” bucket.

Multiple Gaussian processes without for loop?

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ysfoo January 18, 2022, 9:11am 3

Thanks for the welcome! I’ve added a MWE now.

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Multiple Gaussian processes without for loop?

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