Yoo, Jaemin

11 publications

ICML 2025 Aggregation Buffer: Revisiting DropEdge with a New Parameter Block Dooho Lee, Myeong Kong, Sagad Hamid, Cheonwoo Lee, Jaemin Yoo

NeurIPS 2025 Parameter-Free Hypergraph Neural Network for Few-Shot Node Classification Chaewoon Bae, Doyun Choi, Jaehyun Lee, Jaemin Yoo

ICML 2024 Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective Soo Yong Lee, Sunwoo Kim, Fanchen Bu, Jaemin Yoo, Jiliang Tang, Kijung Shin

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

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

NeurIPSW 2024 TSA on AutoPilot: Self-Tuning Self-Supervised Time Series Anomaly Detection Boje Deforce, Meng-Chieh Lee, Bart Baesens, Estefanía Serral Asensio, Jaemin Yoo, Leman Akoglu

ECML-PKDD 2023 DSV: An Alignment Validation Loss for Self-Supervised Outlier Model Selection Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu

TMLR 2023 Data Augmentation Is a Hyperparameter: Cherry-Picked Self-Supervision for Unsupervised Anomaly Detection Is Creating the Illusion of Success Jaemin Yoo, Tiancheng Zhao, Leman Akoglu

ICML 2023 Towards Deep Attention in Graph Neural Networks: Problems and Remedies Soo Yong Lee, Fanchen Bu, Jaemin Yoo, Kijung Shin

IJCAI 2019 Belief Propagation Network for Hard Inductive Semi-Supervised Learning Jaemin Yoo, Hyunsik Jeon, U Kang

NeurIPS 2019 Knowledge Extraction with No Observable Data Jaemin Yoo, Minyong Cho, Taebum Kim, U Kang