25 citations · 28 across the 9 of their papers we have counts for
4 papers · 1 filter
HAiVA: Hybrid AI-assisted Visual Analysis Framework to Study the Effects of Cloud Properties on Climate Patterns
Subhashis Hazarika, Haruki Hirasawa, Sookyung Kim +6
Clouds have a significant impact on the Earth's climate system. They play a vital role in modulating Earth's radiation budget and driving regional changes in temperature and precip…
Climate Intervention Analysis using AI Model Guided by Statistical Physics Principles
Soo Kyung Kim, Kalai Ramea, Salva Rühling Cachay +6
The availability of training data remains a significant obstacle for the implementation of machine learning in scientific applications. In particular, estimating how a system might…
Relationship-aware Multivariate Sampling Strategy for Scientific Simulation Data
Subhashis Hazarika, Ayan Biswas, Phillip J. Wolfram +2
With the increasing computational power of current supercomputers, the size of data produced by scientific simulations is rapidly growing. To reduce the storage footprint and facil…
Deep Learning-Based Feature-Aware Data Modeling for Complex Physics Simulations
Qun Liu, Subhashis Hazarika, John M. Patchett +2
Data modeling and reduction for in situ is important. Feature-driven methods for in situ data analysis and reduction are a priority for future exascale machines as there are curren…