7 citations · 26 across the 12 of their papers we have counts for
13 papers
A Residual Tree Gaussian Process Modeling Framework for High-Dimensional Data
Pulong Ma, Li Ma
With the advance of measurement technologies and increasing computing power, large spatial data with heterogeneous structures are often collected over high-dimensional domains. Exi…
Locally stationary Argo ocean heat content estimates: Modeling, validation and uncertainty quantification
Thea Sukianto, Mikael Kuusela, Donata Giglio +3
Argo profiling floats measure seawater temperature and salinity in the upper 2000 meters of the ocean. These floats are uniquely capable of measuring the global Ocean Heat Content…
Multivariate Gaussian process emulation for multifidelity computer models with high-dimensional spatial outputs
Cyrus S. McCrimmon, Pulong Ma
Risk assessment of hurricane-driven storm surge relies on deterministic computer models that produce outputs over a large spatial domain. The surge models can often be run at a ran…
Asymmetric Space-Time Covariance Functions via Hierarchical Mixtures
Pulong Ma
This work is focused on constructing space-time covariance functions through a hierarchical mixture approach that can serve as building blocks for capturing complex dependency stru…
Analyzing Stochastic Computer Models: A Review with Opportunities
Evan Baker, Pierre Barbillon, Arindam Fadikar +10
In modern science, computer models are often used to understand complex phenomena, and a thriving statistical community has grown around analyzing them. This review aims to bring a…
Computer Model Emulation with High-Dimensional Functional Output in Large-Scale Observing System Uncertainty Experiments
Pulong Ma, Anirban Mondal, Bledar Konomi +3
Observing system uncertainty experiments (OSUEs) have been recently proposed as a cost-effective way to perform probabilistic assessment of retrievals for NASA's Orbiting Carbon Ob…