Weather4cast at NeurIPS 2022: Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts. - Aleksandra Gruca; Federico Serva; Llorenç Lliso; Pilar Rípodas; Xavier Calbet; Pedro Herruzo; Jirí Pihrt; Rudolf Raevskiy; Petr Simánek; Matej Choma; Yang Li; Haiyu Dong; et al. (NeurIPS (Competition and Demos), 2021)

Personalized Graph Summarization: Formulation, Scalable Algorithms, and Applications. - Shinhwan Kang; Kyuhan Lee; Kijung Shin (ICDE, 2022)

Are Edge Weights in Summary Graphs Useful? - A Comparative Study. - Shinhwan Kang; Kyuhan Lee; Kijung Shin (PAKDD (1), 2022)

BeGin: Extensive Benchmark Scenarios and An Easy-to-use Framework for Graph Continual Learning. - Jihoon Ko; Shinhwan Kang; Kijung Shin (CoRR, 2022)

Region-Conditioned Orthogonal 3D U-Net for Weather4Cast Competition. - Taehyeon Kim 001; Shinhwan Kang; Hyeonjeong Shin; Deukryeol Yoon; Seongha Eom; Kijung Shin; Se-Young Yun (CoRR, 2022)

Interplay between topology and edge weights in real-world graphs: concepts, patterns, and an algorithm. - Fanchen Bu; Shinhwan Kang; Kijung Shin (Data Min. Knowl. Discov., 2023)

HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs. - Sunwoo Kim 006; Shinhwan Kang; Fanchen Bu; Soo Yong Lee; Jaemin Yoo; Kijung Shin (ICLR, 2024)

Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy. - Sunwoo Kim 006; Soo Yong Lee; Fanchen Bu; Shinhwan Kang; Kyungho Kim; Jaemin Yoo; Kijung Shin (NeurIPS, 2024)

BeGin: Extensive Benchmark Scenarios and an Easy-to-use Framework for Graph Continual Learning. - Jihoon Ko; Shinhwan Kang; Taehyung Kwon; Heechan Moon; Kijung Shin (ACM Trans. Intell. Syst. Technol., 2025)

RDB2G-Bench: A Comprehensive Benchmark for Automatic Graph Modeling of Relational Databases. - Dongwon Choi; Sunwoo Kim; Juyeon Kim; Kyungho Kim; Geon Lee; Shinhwan Kang; Myunghwan Kim 001; Kijung Shin (CoRR, 2025)