57 citations · 58 across the 6 of their papers we have counts for
6 papers
MARIOH: Multiplicity-Aware Hypergraph Reconstruction
Kyuhan Lee, Geon Lee, Kijung Shin
Hypergraphs offer a powerful framework for modeling higher-order interactions that traditional pairwise graphs cannot fully capture. However, practical constraints often lead to th…
Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data
Jihoon Ko, Kyuhan Lee, Hyunjin Hwang +1
Recently, many deep-learning techniques have been applied to various weather-related prediction tasks, including precipitation nowcasting (i.e., predicting precipitation levels and…
Personalized Graph Summarization: Formulation, Scalable Algorithms, and Applications
Shinhwan Kang, Kyuhan Lee, Kijung Shin
Are users of an online social network interested equally in all connections in the network? If not, how can we obtain a summary of the network personalized to specific users? Can w…
Are Edge Weights in Summary Graphs Useful? -- A Comparative Study
Shinhwan Kang, Kyuhan Lee, Kijung Shin
Which one is better between two representative graph summarization models with and without edge weights? From web graphs to online social networks, large graphs are everywhere. Gra…
Effective Training Strategies for Deep-learning-based Precipitation Nowcasting and Estimation
Jihoon Ko, Kyuhan Lee, Hyunjin Hwang +3
Deep learning has been successfully applied to precipitation nowcasting. In this work, we propose a pre-training scheme and a new loss function for improving deep-learning-based no…
SLUGGER: Lossless Hierarchical Summarization of Massive Graphs
Kyuhan Lee, Jihoon Ko, Kijung Shin
Given a massive graph, how can we exploit its hierarchical structure for concisely but exactly summarizing the graph? By exploiting the structure, can we achieve better compression…