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Tag: gpflow

Is there a way to define a ‘heterogeneous’ kernel design to incorporate linear operators into the regression for GPflow (or GPytorch/GPy/…)?

I’m trying to perform a GP regression with linear operators as described in for example this paper by Särkkä: https://users.aalto.fi/~ssarkka/pub/spde.pdf In this example we can see from equation (8) that I need a different kernel function for the four covariance blocks (of training and test data) in the complete covariance matrix. This is definitely possible and valid, but I would

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