Neural autoregressive flows enable flexible high-dimensional spatial warpings for nonstationary anisotropic processes, with simulations showing greater representational capacity than standard models and an application to 3D Argo Floats data.
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Introduces spSSA extending SSA to spatial data via three generalized eigenvalue procedures and a data augmentation method to estimate nonstationary subspace dimension.
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Modeling nonstationary spatial processes with normalizing flows
Neural autoregressive flows enable flexible high-dimensional spatial warpings for nonstationary anisotropic processes, with simulations showing greater representational capacity than standard models and an application to 3D Argo Floats data.
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Stationary subspace analysis for spatial data
Introduces spSSA extending SSA to spatial data via three generalized eigenvalue procedures and a data augmentation method to estimate nonstationary subspace dimension.