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Advances in Monte Carlo Variational Inference and Applied Probabilistic Modeling

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Figure

Figure 1.1: Example photometric image from the Sloan Digital Sky Survey (SDSS) [Kent et al.].Each pixel in each band represents a noisy photon count, conveying some information about thephysical parameters of the imaged source
Figure 2.1: Linear and Gaussian process regression examples. In both cases the solid area depictsthe posterior distribution over the (noiseless) linear (left) and non-linear (right) functions (withtwo standard deviations visualized)
Figure 2.2 depicts this kind of clustering model and inference. Within X space, we
Figure 3.3: Graphical model representation of the joint photometry and spectroscopy model
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