Gray-box Inference for Structured Gaussian Process Models: Supplementary Material

Gray-box Inference for Structured Gaussian Process Models

We develop an automated variational inference method for Bayesian structured prediction problems with Gaussian process (gp) priors and linear-chain likelihoods. Our approach does not need to know the details of the structured likelihood model and can scale up to a large number of observations. Furthermore, we show that the required expected likelihood term and its gradients in the variational o...

Gaussian Process Regression Networks Supplementary Material

In this supplementary material, we discuss some further details of our ESS and VB inference (Sections 1 and 2), the computational complexity of our inference procedures (Section 3), and the correlation structure induced by the GPRN model (Section 4). We also discuss multimodality in the GPRN posterior (Section 5), SVLMC, and some background information and notation for Gaussian process regressi...

Applications of Abduction #3: \black-box" to \gray-box" Models

Military Operations Research makes extensive use of large complex simulation models. These simulation models are often black-boxes; i.e. they are opaque and incomprehensible. A considerable effort is involved in commissioning a new model into service. We characterise this activity as the construction of gray-box approximate causal models of the functional behaviour of black-box simulation softw...

Supplementary Material: Memoized Online Variational Inference for Dirichlet Process Mixture Models

This document contains supplementary mathematics and algorithm descriptions to help readers understand our new learning algorithm. First, in Sec. 1 we offer detailed model description and update equations for a DP-GMM with zero-mean, full-covariance Gaussian likelihood. Second, in Sec. 2 we provide step-by-step discussion of our birth move algorithm, providing a level-of-detail at which the int...

application of affine gray-box neural models for nonlinear control of chemical processes