GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Jacob Gardner, Geoff Pleiss, Kilian Q. Weinberger, David Bindel, Andrew G. Wilson

Neural Information Processing Systems 

Despite advances in scalable models, the inference tools used for Gaussian processes (GPs) have yet to fully capitalize on developments in computing hardware. We present an efficient and general approach to GP inference based on Blackbox Matrix-Matrix multiplication (BBMM). BBMM inference uses a modified batched version of the conjugate gradients algorithm to derive all terms for training and inference in a single call.

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