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bayesian-warped-dependent-gp
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Markus Kaiser 933db3d9d2
Fix standalone compilation somewhat 		4 years ago
figures Fix labels on warping layer for decomposition plots 5 years ago
poster Fix standalone compilation somewhat 4 years ago
preamble Rework for new camera ready style file 4 years ago
rebuttal Mention Reviewer 1 explicitly 5 years ago
.gitignore Add tikz definitions; Add graphical model 6 years ago
.latexmkrc Start variational formulation 6 years ago
README.md Add readme 6 years ago
additional.bib Add Thomas' feedback 5 years ago
bayesian_warped_dependent_gp.pdf Rework for new camera ready style file 4 years ago
bayesian_warped_dependent_gp.tex Add Clemens' feedback 4 years ago
bayesian_warped_dependent_gp.tex.latexmain Rename paper 6 years ago
deep_probabilistic_workshop.pdf Add precompiled pdfs 6 years ago
deep_probabilistic_workshop.tex Save a few more slides 6 years ago
neurips_2018.sty Rework for new camera ready style file 4 years ago
neurips_2018.tex Rework for new camera ready style file 4 years ago
references.bib Introduction 6 years ago
zotero_export.bib Reformulate the abstract, intro and conclusion 5 years ago

README.md

This paper summarizes a way of formulating priors for multiple functions using GPs. The covariance structure between these processes is assumed to be governed by convolutions over latent processes with non-linear alignment of the different outputs. Both the alignment functions and a warping after the convolutions are learned in the context of a deep GP.

Building the Document

The figures in this paper depend on a newish version of the tikz package. Everything starting with TeX Live 2016 should be fine. Additionally, since they use the graphdrawing library, the document must be built using LuaTeX. The easiest way to build the document is by running latexmk in the main directory - a .latexmkrc-file is provided with the correct configuration. If you want to use a different way of building the document, please make sure to use lualatex.