[Question] Using `GPyTorch` with a distance matrix or covariance matrix as input

Hi! Thanks for providing this nice tool for us!!

My question is it possible to use a symmetric pairwise distance matrix or a covariance matrix from the distance matrix as an input, instead of the conventional used X_train? In the examples given in the documentation, we use use X_train and y_train and the kernel function we select will transform our X_train into a covariance matrix. But in my case, I can only compute the distance matrix.

Any suggestions would be appreciated. Thanks!

[Balandat]

Cool stuff. It should be possible to do this by using the components of the prediction strategies - take a look here: https://github.com/cornellius-gp/gpytorch/blob/master/gpytorch/models/exact_prediction_strategies.py#L249-L264

[FanwangM]

I have an in-house algorithm to get the distance/dissimilarity between two objects. Then I have some objects and I have computed pair-wise distances. This gives me a chance to build a covariance matrix from distance, such as a Matern kernel/covariance. I don’t have coordinates of the objects, which makes the problem a little bit hard to use build-in kernels in gpytorch. I don’t need a complicated kernel. I am looking for something like this in GPyTorch, https://gist.github.com/amueller/1351047.

Hope this is a little bit helpful. @Balandat