activity
20182021
most citedFast and accurate learned multiresolution dynamical downscaling for precipitation

11 citations · 11 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG202111 cited

Fast and accurate learned multiresolution dynamical downscaling for precipitation

Jiali Wang, Zhengchun Liu, Ian Foster +3

This study develops a neural network-based approach for emulating high-resolution modeled precipitation data with comparable statistical properties but at greatly reduced computati…

stat.ML2020

Computer Model Calibration with Time Series Data using Deep Learning and Quantile Regression

Saumya Bhatnagar, Won Chang, Seonjin Kim Jiali Wang

Computer models play a key role in many scientific and engineering problems. One major source of uncertainty in computer model experiment is input parameter uncertainty. Computer m…

stat.ME2019

Ice Model Calibration Using Semi-continuous Spatial Data

Won Chang, Bledar A. Konomi, Georgios Karagiannis +2

Rapid changes in Earth's cryosphere caused by human activity can lead to significant environmental impacts. Computer models provide a useful tool for understanding the behavior and…

stat.AP2018

A Regularized Spatial Market Segmentation Method with Dirichlet Process Gaussian Mixture Prior

Won Chang, Sunghoon Kim, Heewon Chae

Spatially referenced data are increasingly available thanks to the development of modern GPS technology. They also provide rich opportunities for spatial analytics in the field of…

stat.AP2018

Computer model calibration based on image warping metrics: an application for sea ice deformation

Yawen Guan, Christian Sampson, J. Derek Tucker +4

Arctic sea ice plays an important role in the global climate. Sea ice models governed by physical equations have been used to simulate the state of the ice including characteristic…