Stochastic Variational Deep Kernel Learning on Multioutput regression example?

[dajuguan]

📚 Documentation/Examples

I have tested the awesome SVDKL (Stochastic Variational Deep Kernel Learning) on CIFAR10/10, however when I want to tranform it to Multioutput regression on my dataset which has 60,000 records with 78 dim inputs and 72 dim outputs. I always run into errors like this: ''' asset( num_dim == len(x_grid) ''' So it's quite difficult for a beginner to code the Stochastic Variational Deep Kernel Learning on Multioutput regression. I wish you can publish an example, thanks!

• Link to 06_PyTorch_NN_Integration_DKL

[GeorgeDeac]

+1 I want to know how I can achieve 1D output regression with SVDKL can't find any documentation anywhere on the best way to do this..