Neural Likelihoods for Multi-Output Gaussian Processes

31 May 2019Martin JankowiakJacob Gardner

We construct flexible likelihoods for multi-output Gaussian process models that leverage neural networks as components. We make use of sparse variational inference methods to enable scalable approximate inference for the resulting class of models... (read more)

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