1 citations · 3 across the 5 of their papers we have counts for
5 papers
Discovering Spatial Correlations of Earth Observations for weather forecasting by using Graph Structure Learning
Hyeon-Ju Jeon, Jeon-Ho Kang, In-Hyuk Kwon +1
This study aims to improve the accuracy of weather predictions by discovering spatial correlations between Earth observations and atmospheric states. Existing numerical weather pre…
Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention
Van Thuy Hoang, Hyeon-Ju Jeon, O-Joun Lee
Graph Neural Networks (GNNs) update node representations through message passing, which is primarily based on the homophily principle, assuming that adjacent nodes share similar fe…
Halal or Not: Knowledge Graph Completion for Predicting Cultural Appropriateness of Daily Products
Van Thuy Hoang, Tien-Bach-Thanh Do, Jinho Seo +5
The growing demand for halal cosmetic products has exposed significant challenges, especially in Muslim-majority countries. Recently, various machine learning-based strategies, e.g…
Explainable Graph Neural Networks for Observation Impact Analysis in Atmospheric State Estimation
Hyeon-Ju Jeon, Jeon-Ho Kang, In-Hyuk Kwon +1
This paper investigates the impact of observations on atmospheric state estimation in weather forecasting systems using graph neural networks (GNNs) and explainability methods. We…
CloudNine: Analyzing Meteorological Observation Impact on Weather Prediction Using Explainable Graph Neural Networks
Hyeon-Ju Jeon, Jeon-Ho Kang, In-Hyuk Kwon +1
The impact of meteorological observations on weather forecasting varies with sensor type, location, time, and other environmental factors. Thus, quantitative analysis of observatio…