activity
20192023
most citedDeep-dust: Predicting concentrations of fine dust in Seoul using LSTM

9 citations · 15 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2023★ 5 cited

A Domain-Independent Agent Architecture for Adaptive Operation in Evolving Open Worlds

Shiwali Mohan, Wiktor Piotrowski, Roni Stern +4

Model-based reasoning agents are ill-equipped to act in novel situations in which their model of the environment no longer sufficiently represents the world. We propose HYDRA - a f…

cs.LG2023

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…

cs.CV2021

Continuous-Time Video Generation via Learning Motion Dynamics with Neural ODE

Kangyeol Kim, Sunghyun Park, Junsoo Lee +4

In order to perform unconditional video generation, we must learn the distribution of the real-world videos. In an effort to synthesize high-quality videos, various studies attempt…

cs.CV2020

Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation

Sunghyun Park, Kangyeol Kim, Junsoo Lee +4

Video generation models often operate under the assumption of fixed frame rates, which leads to suboptimal performance when it comes to handling flexible frame rates (e.g., increas…

cs.LG2019★ 9 cited

Deep-dust: Predicting concentrations of fine dust in Seoul using LSTM

Sookyung Kim, Jungmin M. Lee, Jiwoo Lee +1

Polluting fine dusts in South Korea which are mainly consisted of biomass burning and fugitive dust blown from dust belt is significant problem these days. Predicting concentration…

physics.comp-ph2019★ 1 cited

Reliable and Explainable Machine Learning Methods for Accelerated Material Discovery

Bhavya Kailkhura, Brian Gallagher, Sookyung Kim +2

Material scientists are increasingly adopting the use of machine learning (ML) for making potentially important decisions, such as, discovery, development, optimization, synthesis…