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11/27/2022
Radial Neighbors for Provably Accurate Scalable Approximations of Gaussian Processes
In geostatistical problems with massive sample size, Gaussian processes ...
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01/25/2022
Spatial meshing for general Bayesian multivariate models
Quantifying spatial and/or temporal associations in multivariate geoloca...
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12/22/2021
Bag of DAGs: Flexible Scalable Modeling of Spatiotemporal Dependence
We propose a computationally efficient approach to construct a class of ...
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01/10/2021
Grid-Parametrize-Split (GriPS) for Improved Scalable Inference in Spatial Big Data Analysis
Rapid advancements in spatial technologies including Geographic Informat...
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12/02/2020
Spatial Multivariate Trees for Big Data Bayesian Regression
High resolution geospatial data are challenging because standard geostat...
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03/25/2020
Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains
We introduce a class of scalable Bayesian hierarchical models for the an...
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09/16/2018