Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes

NeurIPS 2019 Rui Li

This paper studies statistical characteristics of multivariate observations with irregular changes in their covariance structures across input space. We propose a unified nonstationary modeling framework to jointly encode the observation correlations to generate a piece-wise representation with a hyper-level Gaussian process (GP) governing the overall contour of the pieces... (read more)

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