Skip to main content
Statistics
STAT
Statistics
Study
Prospective Students
Current Students
Research
Research Areas
Research Groups
People
All People
Faculty
Affiliate Faculty
Instructional Faculty
Research Scientists
Research Staff
Postdoctoral Fellows
Administrative Staff
Alumni
Students
News
Events
History
Al-Kindi
Al-Kindi Distinguished Statistics Lectures
Al-Kindi Student Awards
About
CEMSE Division
Apply
GPU Computing
Vecchia Approximations of Gaussian Processes on GPUs for Scalable Spatial Modeling and Computer Model Emulation
Qilong Pan, Ph.D. Student, Statistics
May 8, 12:00
-
13:00
B9 L2 R2325
machine learning
Geospatial Data
GPU Computing
This seminar introduces GPU-accelerated Vecchia approximations to overcome Gaussian Process computational limits, enabling scalable applications for large geospatial datasets and high-dimensional computer model emulations.
