Is there a way to perform Gaussian Process Regression on multidimensional output (possibly correlated) using GPML?
In the demo script I could only find a 1D example.
A similar question on CV that tackles case of multidimensional input.
I went through their book to see if I could find anything. In the 9th chapter of this book (section 9.1), they have mentioned this case of multiple outputs. They have mentioned a couple of ways to deal with this, One - using a correlated noise process and Two - Cokriging (Correlated prior).
I still don't know, how I can incorporate any of these ideas into the GPML framework.
Also, are there any other GP libraries/frameworks that support multi-dimensional output?