Publications

Preprints

• [arXiv’23] Class-Imbalanced Learning on Graphs: A Survey
  • Yihong Ma, Yijun Tian, Nuno Moniz, and Nitesh V. Chawla

Conference Papers

• [WWW’24] Are we making much progress? Revisiting chemical reaction yield prediction from an imbalanced regression perspective
  • Yihong Ma, Xiaobao Huang, Bozhao Nan, Nuno Moniz, Xiangliang Zhang, Olaf Wiest, and Nitesh V. Chawla
  • ACM Web Conference, 2024
• [WWW’24] HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks
  • Yihong Ma, Ning Yan, Jiayu Li, Masood Mortazavi, and Nitesh V. Chawla
  • ACM Web Conference, 2024
• [IJCAI’23] Graph-based Molecular Representation Learning
  • Zhichun Guo, Kehan Guo, Bozhao Nan, Yijun Tian, Roshni Iyer, Yihong Ma, Olaf Wiest, Xiangliang Zhang, Wei Wang, Chuxu Zhang, Nitesh V. Chawla
  • International Joint Conference on Artificial Intelligence, 2023
• [CIKM’22] Hierarchical Spatio-Temporal Graph Neural Networks for Pandemic Forecasting
  • Yihong Ma, Patrick Gerard, Yijun Tian, Zhichun Guo, and Nitesh V. Chawla
  • ACM International Conference on Information and Knowledge Management, 2022
• [RE’22] RESAM: A Requirements Discovery Process for Deep Learning based Anomaly Detectors with Applications to UAV Flight Controllers
  • Md Nafee Al Islam, Yihong Ma, Pedro Alarcon Granadeno, Nitesh V. Chawla, and Jane Cleland-Huang
  • IEEE International Conference on Requirements Engineering, 2022
• [IJCAI’22] Multi-modal Recipe Representation Learning with Graph Neural Networks
  • Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald Metoyer, and Nitesh V. Chawla
  • International Joint Conference on Artificial Intelligence, 2022

Journal Papers

• [IntelliSys’23] Detecting Anomalies in Small Unmanned Aerial Systems via Graphical Normalizing Flows
  • Yihong Ma, Md Nafee Al Islam, Jane Cleland-Huang, and Nitesh V. Chawla
  • IEEE Intelligent Systems, 2023
• [TKDE’21] Modeling Co-evolution of Attributed and Structural Information in Graph Sequence
  • Daheng Wang, Zhihan Zhang, Yihong Ma, Tong Zhao, Tianwen Jiang, Nitesh V. Chawla, and Meng Jiang
  • IEEE Transactions on Knowledge and Data Engineering, 2021

Workshop Papers

• [DLG-KDD’20] Learning Attribute-Structure Co-Evolutions in Dynamic Graphs
  • Daheng Wang, Zhihan Zhang, Yihong Ma, Tong Zhao, Tianwen Jiang, Nitesh V. Chawla, and Meng Jiang
  • Workshop on Deep Learning on Graphs at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2020 (Best Paper Award)
• [EYRE-CIKM’19] A Study of Person Entity Extraction and Profiling from Classical Chinese Historiography
  • Yihong Ma, Qingkai Zeng, Tianwen Jiang, Liang Cai, and Meng Jiang
  • Workshop on EntitY REtrieval at ACM International Conference on Information and Knowledge Management, 2019