331 * !
Tue, 7/30/2019,
10:30 AM -
12:20 PM
CC-709
Advances in the Analysis of Massive Space-Time Data Sets Using High Performance Computing — Topic Contributed Papers
Section on Statistics and the Environment , Section on Teaching of Statistics in the Health Sciences
Organizer(s): Florian Gerber, Colorado School of Mines
Chair(s): Joseph Guinness, Cornell University
10:35 AM
Implementing Spatial Statistical Methods for Massive Data
Dorit Hammerling, National Center for Atmospheric Research ; Huang Huang, National Center for Atmospheric Research; Lewis Blake, Colorado School of Mines
10:55 AM
Scalable Gapfilling in Spatio-Temporal Remote Sensing Data
Reinhard Furrer, University of Zurich
11:15 AM
Detecting Changes in Precipitation Extremes at Their Native Scales Over the Contiguous United States
Mark Risser, Lawrence Berkeley National Laboratory ; Christopher Paciorek, University of California; Michael Wehner, Lawrence Berkeley National Laboratory; Travis O'Brien, Lawrence Berkeley National Laboratory; William Collins, Lawrence Berkeley National Laboratory
11:35 AM
Nonstationary Spatial Data: Think Globally Act Locally
Douglas William Nychka, NCAR
11:55 AM
GPU Accelerated Deep Learning for Climate and Weather
David Hall, NVIDIA
12:15 PM
Floor Discussion