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cs.LG2025
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…
cs.LG2024★ 1 cited
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…
cs.LG2023★ 2 cited
Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity
Van Thuy Hoang, O-Joun Lee
Graph representation learning (GRL) methods, such as graph neural networks and graph transformer models, have been successfully used to analyze graph-structured data, mainly focusi…