Conditional Graph Information Bottleneck for Molecular Relational Learning. - Namkyeong Lee; Dongmin Hyun; Gyoung S. Na; Sungwon Kim 002; Junseok Lee 002; Chanyoung Park 001 (ICML, 2023)

Task-Equivariant Graph Few-shot Learning. - Sungwon Kim 002; Junseok Lee 002; Namkyeong Lee; Wonjoong Kim; Seungyoon Choi; Chanyoung Park 001 (KDD, 2023)

Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer. - Namkyeong Lee; Heewoong Noh; Sungwon Kim 002; Dongmin Hyun; Gyoung S. Na; Chanyoung Park 001 (NeurIPS, 2023)

Interpretable Prototype-based Graph Information Bottleneck. - Sangwoo Seo; Sungwon Kim 002; Chanyoung Park 001 (NeurIPS, 2023)

Predicting Density of States via Multi-modal Transformer. - Namkyeong Lee; Heewoong Noh; Sungwon Kim 002; Dongmin Hyun; Gyoung S. Na; Chanyoung Park 001 (CoRR, 2023)

Unsupervised Episode Generation for Graph Meta-learning. - Jihyeong Jung; Sangwoo Seo; Sungwon Kim 002; Chanyoung Park 001 (ICML, 2024)

Self-Explainable Temporal Graph Networks based on Graph Information Bottleneck. - Sangwoo Seo; Sungwon Kim 002; Jihyeong Jung; Yoonho Lee 002; Chanyoung Park 001 (KDD, 2024)

DSLR: Diversity Enhancement and Structure Learning for Rehearsal-based Graph Continual Learning. - Seungyoon Choi; Wonjoong Kim; Sungwon Kim 002; Yeonjun In; Sein Kim; Chanyoung Park 001 (WWW, 2024)

Subgraph Federated Learning for Local Generalization. - Sungwon Kim 002; Yoonho Lee 002; Yunhak Oh; Namkyeong Lee; Sukwon Yun; Junseok Lee 002; Sein Kim; Carl Yang 001; Chanyoung Park 001 (ICLR, 2025)