1 citations · 1 across the 5 of their papers we have counts for
5 papers
Temporal Coverage over Density: Parsimonious Training-Set Design for ML Climate Downscaling
Karandeep Singh, Stefan Rahimi, Chad W. Thackeray +2
High-resolution regional climate simulations provide critical information for climate impacts assessments but remain computationally expensive, motivating the development of machin…
Self Supervised Vision for Climate Downscaling
Karandeep Singh, Chaeyoon Jeong, Naufal Shidqi +4
Climate change is one of the most critical challenges that our planet is facing today. Rising global temperatures are already bringing noticeable changes to Earth's weather and cli…
Generating High-Resolution Regional Precipitation Using Conditional Diffusion Model
Naufal Shidqi, Chaeyoon Jeong, Sungwon Park +3
Climate downscaling is a crucial technique within climate research, serving to project low-resolution (LR) climate data to higher resolutions (HR). Previous research has demonstrat…
GraphFC: Customs Fraud Detection with Label Scarcity
Karandeep Singh, Yu-Che Tsai, Cheng-Te Li +2
Custom officials across the world encounter huge volumes of transactions. With increased connectivity and globalization, the customs transactions continue to grow every year. Assoc…
Active Learning for Human-in-the-Loop Customs Inspection
Sundong Kim, Tung-Duong Mai, Sungwon Han +5
We study the human-in-the-loop customs inspection scenario, where an AI-assisted algorithm supports customs officers by recommending a set of imported goods to be inspected. If the…