2 citations · 5 across the 15 of their papers we have counts for
6 papers · 1 filter
Fisher Scoring for Exact Matérn Covariance Estimation through Stable Smoothness Optimization
Yiping Hong, Sameh Abdulah, Marc G. Genton +1
Gaussian Random Fields (GRFs) with Matérn covariance functions have emerged as a powerful framework for modeling spatial processes due to their flexibility in capturing different f…
Block Vecchia Approximation for Scalable and Efficient Gaussian Process Computations
Qilong Pan, Sameh Abdulah, Marc G. Genton +1
Gaussian Processes (GPs) are vital for modeling and predicting irregularly-spaced, large geospatial datasets. However, their computations often pose significant challenges in large…
Boosting Earth System Model Outputs And Saving PetaBytes in their Storage Using Exascale Climate Emulators
Sameh Abdulah, Allison H. Baker, George Bosilca +9
We present the design and scalable implementation of an exascale climate emulator for addressing the escalating computational and storage requirements of high-resolution Earth Syst…
MPCR: Multi-Precision Computations Package in R
Mary Lai O. Salvana, Sameh Abdulah, Minwoo Kim +3
In the early days of computing, severe memory constraints made it necessary to use lower floating-point precision. As hardware capabilities have advanced, modern systems, particula…
GPU-Accelerated Vecchia Approximations of Gaussian Processes for Geospatial Data using Batched Matrix Computations
Qilong Pan, Sameh Abdulah, Marc G. Genton +3
Gaussian processes (GPs) are commonly used for geospatial analysis, but they suffer from high computational complexity when dealing with massive data. For instance, the log-likelih…
On the Impact of Spatial Covariance Matrix Ordering on Tile Low-Rank Estimation of Matérn Parameters
Sihan Chen, Sameh Abdulah, Ying Sun +1
Spatial statistical modeling and prediction involve generating and manipulating an n*n symmetric positive definite covariance matrix, where n denotes the number of spatial location…