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stat.ML2018★ 45 cited
Structured Bayesian Gaussian process latent variable model: applications to data-driven dimensionality reduction and high-dimensional inversion
Steven Atkinson, Nicholas Zabaras
We introduce a methodology for nonlinear inverse problems using a variational Bayesian approach where the unknown quantity is a spatial field. A structured Bayesian Gaussian proces…
stat.ML2018★ 7 cited
Structured Bayesian Gaussian process latent variable model
Steven Atkinson, Nicholas Zabaras
We introduce a Bayesian Gaussian process latent variable model that explicitly captures spatial correlations in data using a parameterized spatial kernel and leveraging structure-e…